CN117291654A - Energy storage participation market scheduling optimization method and device considering full life cycle cost - Google Patents
Energy storage participation market scheduling optimization method and device considering full life cycle cost Download PDFInfo
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Abstract
The invention discloses an energy storage participation market scheduling optimization method and device considering the cost of a whole life cycle, comprising the following steps: dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously combining the existing energy storage power station to participate in spot market and frequency modulation market mechanisms to construct the energy storage participation market transaction scheduling structure description; constructing a profit measuring and calculating model of energy storage participation in spot market; constructing a comprehensive index; the comprehensive index is used as a gain calculation model for dividing energy storage to participate in the frequency modulation market; constructing an energy storage power station construction cost analysis model; determining a scheduling strategy model considering the whole life cycle of the energy storage based on the energy storage participating in the operation of the electric energy market and the auxiliary service market and aiming at maximizing the income; and solving the scheduling strategy model by adopting CPLEX to obtain a market scheduling strategy which takes the energy storage life cycle into account. The invention provides a component analysis strategy considering the total life cycle of energy storage, and a comprehensive energy storage participation market dispatching optimization method is provided.
Description
Technical Field
The invention relates to the technical field of energy storage participation market dispatching optimization, in particular to an energy storage participation market dispatching optimization method and device considering the total life cycle cost.
Background
With the construction of a novel power system, the installation duty ratio of new energy is continuously increased, the duty ratio of a traditional thermal power and other reliable power supply is gradually reduced, the influence of extreme climate on the water and electricity output is overlapped, and the response and adjustment capability of the power system are greatly weakened. The energy storage power station can fully meet the requirement of load regulation by virtue of the quick response capability, and has important roles in promoting the high-proportion consumption of new energy, guaranteeing the safe supply of electric power and improving the operation efficiency of an electric power system, thereby becoming a key link for the construction of a novel electric power system in the future.
The current energy storage power station has the problems of high investment cost, low return rate, weak social investment will and the like, and along with the acceleration of the development of the electric power market, the energy storage power station has the problems of insufficient connection with the market development, insufficient excitation constraint mechanism and the like. Meanwhile, peak-valley electricity prices related to the development of large-scale energy storage, auxiliary service markets, and repairing policies related to the energy storage are difficult to support the energy storage to obtain stable income so as to realize cost recovery. In addition, the practical economic value of the energy storage power station participating in the functions of peak shaving, frequency modulation and the like of the power grid is difficult to realize stable income through the existing market mechanism and system operation mode.
At present, most of built energy storage power stations can bear the demands of frequency modulation and peak shaving of a power grid, but the existing scheduling scheme is immature and unbalanced, so that the energy storage power stations are difficult to meet the design demands of the optimized power grid, and energy storage resources are wasted. Meanwhile, the development of the energy storage power station is greatly influenced by the imperfect operation strategy of auxiliary service functions such as peak shaving, frequency modulation and the like. Thus, there is a need for intensive research into how to fully exploit the optimal scheduling role of energy storage power stations in power grid systems.
In the aspect of energy storage cost analysis, the current cost benefit analysis of the energy storage power station is mainly focused on the construction of an energy storage power station system economic evaluation model, and the economic benefits of different schemes are comprehensively evaluated by considering a plurality of factors such as construction cost, operation and maintenance cost, energy storage power, electric energy discharge power and the like. However, the problems of relatively low economical efficiency of the energy storage power station, lack of effective coordination between the energy storage power station and the electric power market and the like exist in China at present.
Disclosure of Invention
The invention aims to provide an energy storage participation market dispatching optimization method and device considering the total life cycle cost, constructs a revenue measuring and calculating model of two systems of energy storage participation spot market and frequency modulation market, provides a component analysis strategy considering the total life cycle of energy storage, and comprehensively constructs the energy storage participation market dispatching optimization method so as to provide an effective path for the operation mode of an energy storage power station in China.
The invention is realized by the following technical scheme:
in a first aspect, the present invention provides a method of energy storage participation market schedule optimization accounting for full life cycle costs, the method comprising:
dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously combining the existing energy storage power station to participate in spot market and frequency modulation market mechanisms to construct the energy storage participation market transaction scheduling structure description;
constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
constructing comprehensive indexes according to the characteristics of different energy storage power stations, the response time, the adjustment speed and the peak clipping and valley filling effect indexes; the comprehensive index is used as the profit of dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model of the energy storage to participate in the frequency modulation market is obtained;
constructing an energy storage power station construction cost analysis model according to the total life cycle cost of the energy storage power station;
determining a scheduling strategy model considering the whole life cycle of the energy storage based on the energy storage participating in the operation of the electric energy market and the auxiliary service market and aiming at maximizing the income;
and solving the scheduling strategy model by adopting a CPLEX technology to obtain a market-participating scheduling strategy considering the energy storage life cycle.
Further, the expression of the comprehensive index is:
wherein K is i For the comprehensive frequency modulation performance index epsilon of the frequency modulation resource in the ith scheduling period 1 Is thatWeight coefficient, epsilon 2 Is->Weight coefficient, epsilon 3 Is->Weight coefficient of (2); />The response time of the frequency modulation resource in the ith scheduling period is given, and k is the total number of frequency modulation instructions sent in the ith scheduling period; t is t i,j Responding the time of the j-th frequency modulation instruction in the i-th scheduling period for the frequency modulation resource; />For the adjustment speed, v, of the frequency modulation resource in the ith scheduling period sta Standard tuning speeds given for the frequency modulation market; />The actual regulation speed of the frequency modulation resource in response to the jth frequency modulation instruction in the ith scheduling period;for the adjustment accuracy of the FM resource in the ith scheduling period,/th scheduling period>And->And respectively responding the required output and the actual output of the j-th frequency modulation instruction in the i-th scheduling period for the frequency modulation resource.
Further, the direct benefit index refers to the benefit directly generated after the operation of the energy storage system, and comprises the difference benefit, the clean energy electricity benefit and the patch benefit of the high-price release of the electric energy in low-price storage;
the indirect benefit index refers to benefits brought by delaying equipment investment on the power grid side through configuration of a pure coagulation system.
Further, the scheduling policy model is:
wherein t is a time point sequence number; n is a annual scheduling period; r is R cap Representing daily capacity gain, R mil Representing the daily mileage gain; r is R total Representing total income of the energy storage power station in the spot market; c is the full life cycle cost of the energy storage power station.
Further, the CPLEX technology is adopted to solve the scheduling strategy model, which comprises the following steps:
inputting initial data to a scheduling strategy model, wherein the initial data comprises the life cycle of an energy storage power station, construction cost parameters, transaction parameters, discount rate and the like;
considering the cost of the energy storage life cycle, the total earnings of spot and frequency modulation markets, taking the maximized earnings as an objective function, and constructing constraint conditions for a scheduling strategy model;
and solving the scheduling strategy model by adopting a CPLEX technology to obtain a market-participating scheduling strategy considering the energy storage life cycle.
Further, the participation market scheduling strategy that accounts for the energy storage life cycle includes the amount of participation in the spot market and the frequency modulated market at each time of energy storage, and the charge and discharge schedule.
Further, the constraint includes:
k down ≤S soc,t ≤k up (26)
-ΔP i ≤P i,t -P i,t-1 ≤ΔP i (27)
wherein, the formula (21) and the formula (22) are respectively the constraint of the system frequency modulation capacity requirement and the mileage requirement,and->Respectively representing the system leveling capacity requirement and the mileage requirement which are required to be met in the period t; equation (23) represents the winning capacity C in ACG of time period t resource i i,t ACG available frequency modulation capacity of its declaration must not be exceeded +.>Formula (24) shows the output of time period t resource i in the spot market +.>Sum of bid-winning capacities C in FM auxiliary services market i,t Must be at its own lower limit of force P i min And an upper limit P i max Within the range; formula (25) shows that in any response, a specific resource can be in either up-or down-regulated state,/or>And->The up-frequency modulation or down-frequency modulation zone bit of the resource i when responding to the frequency modulation instruction signal for the jth time is respectively 0-1 variableWhen the value is 1, the corresponding frequency modulation state is operated, and when the value is 0, the corresponding frequency modulation state is not operated; equation (26) is the SOC constraint of the stored energy, S soc,t SOC, k for time period t down And k up The lower limit and the upper limit of the SOC are respectively; equation (27) is climbing constraint of frequency modulation resource, P i,t And P i,t-1 The sum of the output of the time period t and the t-1 resource i in the energy market and the frequency modulation auxiliary service market is delta P i The output force for resource i to allow to rise and fall in a period of time can be determined by querying the climbing rate of different types of resources.
In a second aspect, the present invention further provides an energy storage participation market scheduling optimization device that accounts for full life cycle costs, the device using the energy storage participation market scheduling optimization method that accounts for full life cycle costs described above; the device comprises:
the energy storage participation market transaction scheduling structure construction unit is used for dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously constructing the energy storage participation market transaction scheduling structure description by combining the existing energy storage power station participation spot market and frequency modulation market mechanism;
the energy storage participation spot market measuring and calculating unit is used for constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
the energy storage participation frequency modulation market measuring and calculating unit is used for constructing comprehensive indexes according to the indexes of different energy storage power station characteristics, response time, adjustment speed and peak clipping and valley filling effects; the comprehensive index is used as the profit of dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model of the energy storage to participate in the frequency modulation market is obtained;
the energy storage power station full life cycle cost analysis unit is used for constructing an energy storage power station construction cost analysis model according to the energy storage power station full life cycle cost;
the scheduling strategy model determining unit is used for determining a scheduling strategy model considering the whole life cycle of the energy storage based on the fact that the energy storage participates in the operation of the electric energy market and the auxiliary service market and aims at maximizing the income;
and the scheduling strategy solving unit is used for solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
In a third aspect, the present invention further provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the energy storage participation market scheduling optimization method described above in view of full life cycle costs when executing the computer program.
In a fourth aspect, the present invention further provides a computer readable storage medium storing a computer program, where the computer program when executed by a processor implements the energy storage participation market scheduling optimization method described above that accounts for full life cycle costs.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention relates to an energy storage participation market dispatching optimization method and device for considering the total life cycle cost, which aims to ensure the stable operation of a power grid and promote the sustainable development of the power grid, and aims to analyze and evaluate the construction cost benefit of a domestic energy storage power station in consideration of the total life cycle theory, consider the participation market of the energy storage power station in spot market and the income of a frequency modulation market, fully mobilize the participation market as the aim, calculate the income obtained by the energy storage power station and form a frequency modulation dispatching strategy for maximizing the income of the energy storage power station. Specifically, a revenue measuring and calculating model of two electricity prices of the energy storage participation spot market and the frequency modulation market is constructed, a component analysis strategy considering the whole life cycle of the energy storage is provided, and the energy storage participation market dispatching optimization method is comprehensively formed so as to provide an effective path for the operation mode of the energy storage power station in China.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
FIG. 1 is a flow chart of an energy storage participation market scheduling optimization method accounting for full life cycle costs of the present invention;
FIG. 2 is a diagram depicting the energy storage participation market transaction scheduling architecture of the present invention;
FIG. 3 is a flow chart of a dispatch optimization model solution of the present invention;
FIG. 4 is a block diagram of an energy storage participation market schedule optimizing apparatus of the present invention accounting for full life cycle costs.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
At present, most of built energy storage power stations can bear the demands of frequency modulation and peak shaving of a power grid, but the existing scheduling scheme is immature and unbalanced, so that the energy storage power stations are difficult to meet the design demands of the optimized power grid, and energy storage resources are wasted. Meanwhile, the development of the energy storage power station is greatly influenced by the imperfect operation strategy of auxiliary service functions such as peak shaving, frequency modulation and the like. Thus, there is a need for intensive research into how to fully exploit the optimal scheduling role of energy storage power stations in power grid systems.
In the aspect of energy storage cost analysis, the current cost benefit analysis of the energy storage power station is mainly focused on the construction of an energy storage power station system economic evaluation model, and the economic benefits of different schemes are comprehensively evaluated by considering a plurality of factors such as construction cost, operation and maintenance cost, energy storage power, electric energy discharge power and the like. However, the problems of relatively low economical efficiency of the energy storage power station, lack of effective coordination between the energy storage power station and the electric power market and the like exist in China at present.
Therefore, the invention aims at guaranteeing the stable operation of the power grid and promoting the sustainable development of the power grid, considers the whole life cycle theory, analyzes and evaluates the construction cost benefit of the domestic energy storage power station, considers the benefits of the energy storage power station in the spot market and the frequency modulation market, aims at fully mobilizing the energy storage participation market, calculates the benefits obtained by the energy storage power station, and forms a frequency modulation scheduling strategy for maximizing the benefits of the energy storage power station.
Specifically, the invention relates to an energy storage participation market dispatching optimization method and device considering the total life cycle cost, constructs a revenue measuring and calculating model of two electricity prices of an energy storage participation spot market and a frequency modulation market, provides a component analysis strategy considering the total life cycle of the energy storage, and comprehensively forms the energy storage participation market dispatching optimization method so as to provide an effective path for the operation mode of an energy storage power station in China.
Example 1
As shown in fig. 1, the present invention relates to a method for optimizing energy storage participation market scheduling considering full life cycle cost, the method comprises:
s1, dividing the construction cost of an energy storage power station into service years of the energy storage power station, and simultaneously constructing a description of a transaction scheduling structure of the energy storage participation market by combining the existing mechanism of the energy storage power station participating in the spot market and the frequency modulation market;
the main purpose of the invention is to maximize the benefits of energy storage participation in the market. However, because the construction cost only exists in the initial stage, the power station profit is a long-term process, and the traditional measuring and calculating scheme with equal total amount is not in accordance with the actual situation due to the difference of time scales, the invention introduces a full life cycle theory in the aspect of measuring and calculating the construction cost of the energy storage power station, divides the construction cost of the energy storage power station into service years of the energy storage power station, simultaneously only considers single-stage profit of the frequency modulation market or spot market in the prior art, does not combine the existing energy storage power station to participate in the spot market and the frequency modulation market mechanism, and comprehensively measures and calculates the profit of the energy storage power station, therefore, in the aspect of measuring and calculating the profit, the invention considers the energy storage power station to participate in the spot market and the frequency modulation market mechanism, and analyzes the trading strategy of the energy storage participation in the electric energy and the frequency modulation auxiliary service market. FIG. 2 is a block diagram of a method for energy storage participation in market scheduling optimization.
S2, constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
the prior art only considers the direct electricity selling benefits of the energy storage as an electricity selling party aiming at the benefits of the energy storage in the spot market, and does not consider the clean benefits and investment benefits of the energy storage electric quantity. Therefore, the invention divides the energy storage participation in spot market benefit into direct benefit and indirect benefit. The direct benefit refers to economic benefit directly generated after the operation of the energy storage system, and mainly comprises difference benefit, clean energy electricity benefit and patch benefit of high-price release of electric energy in low-price storage. The indirect benefit refers to the benefit brought by delaying the investment of equipment at the power grid side by configuring a pure condensing system, and is specifically calculated as follows:
first, low storage and high delivery operating benefits. At peak-to-valley electricity prices, the energy storage device is charged at low load peak-to-valley, lower electricity prices, and discharged at high load peak-to-peak, higher electricity prices. The economic benefit annual value earned by the time-sharing electricity price of the energy storage under the operation mode is the low-energy-storage high-emission operation benefit:
wherein R is op Representing the low storage and high-delivery operational benefits of the energy storage system. P is p s Representing peak time discharge price; p is p f Representing the discharge price of the ordinary period; p is p v,chr Representing the charging electricity price in the valley period;representing the peak period discharge capacity; />Representing the discharge electric quantity of the ordinary period; />And->Respectively representing the valley period and the flat period of the charging electric quantity; η represents the energy storage charging efficiency.
Second, clean energy and electricity benefits. The clean energy electric quantity benefit provided by the invention means that the energy storage system can store the surplus output of new energy and then release the stored electric energy in the load peak time, so that the amount of abandoned wind and abandoned light can be reduced, and the system benefit is increased.
R power ＝p wind E wind +p Photovoltaic E Photovoltaic (2)
Wherein R is power Representing the electric quantity benefit of the energy storage system; p is p wind And p Photovoltaic Respectively representing wind power and photovoltaic power generation internet electricity prices; e (E) wind And E is Photovoltaic Respectively representing the new energy electric quantity which is admitted after the energy storage system is configured.
Thirdly, the investment income of the power grid is delayed. With the development of economy and society, the power grid needs to increase investment according to the increase condition of load demands, so that the capacity of the power grid is enlarged, and the stability of energy supply is improved. The energy storage system has peak clipping and valley filling effects, can relieve the load pressure of the power grid in the peak period, and indirectly delays the capacity extension of the power grid.
R de ＝γ de C de η Pde Q ESS (3)
Wherein R is de Indicating delay of investment income of the power grid; gamma ray de Representing a fixed asset depreciation rate of a power transmission and distribution facility; c (C) de Representing the cost per unit volume; η (eta) Pde Representing the efficiency of the energy storage system, which is caused by the loss of energy storage charge and discharge and the loss of equipment access network; q (Q) ESS Representing the energy storage extension capacity.
Fourth, energy storage participates in spot market total revenue.
Based on the analysis, the comprehensive benefits of the operation of the energy storage system can be established by measuring and calculating benefits of the energy storage system in low-storage high-delivery operation benefits, electric quantity benefits, subsidy benefits, deferred investment benefits of the power grid, residual values of the energy storage system and the like. When the profit of the energy storage system is calculated, the optimal peak-valley time-of-use electricity price is calculated according to the investment recovery expectations of a decision maker, and the method specifically comprises the following steps of:
R total ＝R op +R power +R de (4)
wherein R is total Indicating that the energy storage system is participating in the spot market total revenue.
S3, constructing comprehensive indexes according to the characteristics of different energy storage power stations, the response time, the adjustment speed and the peak clipping and valley filling effect indexes; the comprehensive index is used as the profit of dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model of the energy storage to participate in the frequency modulation market is obtained;
the prior art mainly focuses on mileage gain and capacity gain aiming at gain measurement of energy storage participating in frequency modulation market. However, the response time, the adjustment speed and the peak clipping and valley filling effects of different energy storage power stations are obviously different, and the energy storage participation frequency modulation market benefit is obviously not fair enough only in an average distribution mode, so that the comprehensive index is constructed according to the characteristics of the different energy storage power stations, the response time, the adjustment speed and the peak clipping and valley filling effect index, and the comprehensive index is used as the benefit for dividing the energy storage participation frequency modulation market, so that the benefit calculation of the energy storage power stations is fair and reasonable.
First, the index is synthesized. In order to embody the advantages of energy storage in the frequency modulation market and simultaneously measure the cost paid by the action of energy storage frequency modulation, the invention adopts the comprehensive frequency modulation performance index to measure the frequency modulation effect, and comprehensively evaluates the frequency modulation performance in 3 aspects of response time, adjustment speed and peak clipping and valley filling effect index.
(1) Response time. The response time refers to delay time of the frequency modulation resource when the frequency modulation command is received and the specified required output direction is consistent, namely time of the frequency modulation resource crossing the adjustment dead zone. In view of the process of energy storage responding to the frequency modulation signal, the ratio of the dead time of frequency modulation resource crossing adjustment to the total flow time of responding to the frequency modulation instruction is adopted to quantify the response time.
Wherein t is i,j For the time that the frequency modulated resource responds to the jth frequency modulated instruction in the ith scheduling period,adjusting the dead time, + for the frequency modulated resource in response to crossing of the jth frequency modulated instruction in the ith scheduling period>And->The starting time and the ending time of the frequency modulation resource responding to the j-th frequency modulation instruction in the i-th scheduling period are respectively.
Considering that a plurality of frequency modulation instructions are contained in one scheduling period, the response time of the frequency modulation resource is determined by taking the average value of the response time of each frequency modulation instruction.
In the method, in the process of the invention,and k is the total number of the frequency modulation instructions sent out in the ith scheduling period.
(2) The speed is adjusted. The regulation speed refers to the speed of the frequency modulation resource reaching the instruction required output when receiving the frequency modulation instruction, and mainly depends on the standard regulation speed set by the frequency modulation market and the actual regulation speed of the frequency modulation resource.
In the method, in the process of the invention,for the actual modulation speed of the modulation resource in response to the jth modulation command in the ith scheduling period,and->And respectively responding the initial output and the end output of the j-th frequency modulation instruction of the frequency modulation resource in the i-th scheduling period.
In the method, in the process of the invention,for the adjustment speed, v, of the frequency modulation resource in the ith scheduling period sta Standard tuning speeds are given for the frequency modulation market.
(3) And (5) adjusting the precision. The adjustment precision refers to the deviation degree of the actual output of the frequency modulation resource and the required output of the frequency modulation instruction. The invention adopts the ratio of the maximum deviation value and the average deviation value of the required output and the actual output of the frequency modulation command to quantify the adjustment precision of the frequency modulation resource, and determines the adjustment precision of the frequency modulation resource in one period by solving the average value of the adjustment precision of each scheduling command.
In the method, in the process of the invention,for the adjustment accuracy of the FM resource in the ith scheduling period,/th scheduling period>And->And respectively responding the required output and the actual output of the j-th frequency modulation instruction in the i-th scheduling period for the frequency modulation resource.
(4) And (5) synthesizing indexes. The comprehensive index is determined by the 3 frequency modulation performance indexes, and the relative importance degree of different adjustment indexes is measured by setting weight coefficients.
Wherein K is i For the comprehensive frequency modulation performance index epsilon of the frequency modulation resource in the ith scheduling period 1 Is thatWeight coefficient, epsilon 2 Is->Weight coefficient, epsilon 3 Is->Weight coefficient of (c) in the above-mentioned formula (c).
Second, capacity benefits and mileage benefits. The actual settlement process is the accumulation of the benefits of each settlement period, and because the running effects of each frequency modulation resource are different in practice, the comprehensive frequency modulation performance index of each frequency modulation resource is considered when the benefits are calculated, and the daily capacity benefits R are obtained cap And mileage benefit R mil The method comprises the following steps of:
wherein C is ES,t Winning capacity for time period t energy storage, M ES,t Frequency modulation mileage marked for time period t energy storage, K ES,t For the comprehensive frequency modulation performance index of the energy storage of the period t,and->And unifying clear capacity price and mileage price for the period t market respectively.
S4, constructing an energy storage power station construction cost analysis model according to the total life cycle cost of the energy storage power station;
from the whole life cycle perspective, an energy storage system model based on an average cost analysis method is provided, and mainly comprises five parts of initial investment cost, operation maintenance cost, electricity replacement cost, other cost and residual recovery value.
d1. Initial investment costs. The initial investment cost refers to fixed funds which are input at one time in the initial stage of an engineering head key of the energy storage system, and are generally used for purchasing main equipment, namely:
wherein: c (C) inv The fixed investment cost for energy storage; c p Cost coefficient for unit power; p (P) ESS Rated charge/discharge power for energy storage; c e Cost coefficient for energy storage unit capacity; e (E) ESS And N is the full life cycle of the energy storage power station.
d2. Running and maintenance costs. The operation and maintenance costs refer to funds dynamically invested for ensuring the normal operation of the energy storage system in the life span, and generally comprise the costs of testing, installing, wearing, stopping, manpower, overhauling, maintaining and the like of the energy storage system, and the costs are taken as a unit of year, namely:
C OM ＝K O P ESS +K M Q ESS (14)
wherein: k (K) O Maintaining a cost coefficient for annual operation of unit power of energy storage; k (K) M The annual operation maintenance cost coefficient of the unit capacity of the energy storage; q (Q) ESS Annual energy production for energy storage.
When the annual operation cost coefficient and the annual maintenance cost coefficient of the stored energy are not easy to determine, the operation maintenance cost is generally estimated approximately according to a certain proportion of the initial investment, namely
Wherein: mu (mu) OM The scale factor of the maintenance cost for the operation of the energy storage power station is generally 3%.
d3. And (5) electricity exchanging cost. Considering that the performance of the energy storage battery gradually decreases along with the increase of the using times, when the performance of the energy storage battery is difficult to meet the requirement of the energy storage power station, the service life of the energy storage power station can be prolonged by replacing the battery in the energy storage power station, the investment utilization efficiency of the energy storage power station is improved, and the investment recovery period is shortened, namely:
wherein: c (C) R Sigma for the electricity change cost R The power conversion cost coefficient is the unit capacity, and l is the power conversion year.
d4. Other costs. The energy storage power station cost also comprises financial cost, tax and other costs, and is calculated according to a certain proportion of investment cost, namely:
wherein: gamma ray o For other cost factors, 10% is typically taken.
d5. And the recovery value is remained. When the service life of each part of elements of the energy storage power station is exhausted, innocent treatment is needed, and the invested funds are disposal cost. The cost is mainly divided into two aspects: environmental expense and equipment residue. Typically, the cost of energy storage battery recycling is an environmental expenditure, and the initial investment cost and recycling coefficient (related to frequency and age) will determine the size of the non-energy storage battery device residuals. The energy storage plant disposal cost can be expressed as:
wherein: gamma ray 1 The power recovery coefficient of the energy storage battery; gamma ray 2 Gamma, the energy recovery coefficient of the energy storage battery 3 To recover the residual coefficient.
d6. Overall cost. In summary, the above 5 aspects, the full life cycle cost of the energy storage power station, C:
C＝C inv +C OM +C site +C o -C re (19)
s5, determining a scheduling strategy model considering the whole life cycle of the energy storage based on the energy storage participating in the operation of the electric energy market and the auxiliary service market and aiming at maximizing the income; the scheduling policy model is:
wherein t is a time point sequence number; n is a annual scheduling period; r is R cap Representing daily capacity gain, R mil Representing the daily mileage gain; r is R total Representing total income of the energy storage power station in the spot market; c is the full life cycle cost of the energy storage power station.
And S6, solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
The scheduling strategy model takes the energy of the energy storage participation electric energy and the frequency modulation market capacity as decision variables, other parameters are input into the model according to historical data of the energy storage power station, construction facility parameters and the like, constraint conditions of the energy storage power station when participating in market transaction are considered, and the maximum income is taken as an objective function to solve the operation strategy of the energy storage participation market. As shown in fig. 3, the specific steps are as follows:
step one: initial data is entered into the scheduling policy model. And inputting initial data such as life cycle, construction cost parameters, transaction parameters, discount rate and the like of the energy storage power station.
Step two: and taking the cost, spot and total market profits of the energy storage life cycle into consideration, taking the maximized profits as an objective function, and constructing constraint conditions for the scheduling strategy model. The maximum benefit is taken as an objective function. In terms of cost, the initial investment cost, the operation maintenance cost, the electricity replacement cost, other costs and the residual recovery value of the energy storage power station are considered. In the aspect of earnings, spot market earnings, capacity earnings and mileage earnings are considered, and meanwhile, system frequency modulation capacity requirements and mileage requirement constraint, unit capacity, power, climbing constraint, energy storage SOC constraint and resource frequency modulation state constraint are set.
Specifically, constraint conditions mainly comprise constraint of system frequency modulation capacity requirement and mileage requirement, constraint of unit capacity, power, climbing, constraint of energy storage SOC and constraint of resource frequency modulation state, and specifically comprise:
k down ≤S soc,t ≤k up (26)
-ΔP i ≤P i,t -P i,t-1 ≤ΔP i (27)
wherein, the formula (21) and the formula (22) are respectively the constraint of the system frequency modulation capacity requirement and the mileage requirement,and->Respectively representing the system leveling capacity requirement and the mileage requirement which are required to be met in the period t; equation (23) represents the winning capacity C in ACG of time period t resource i i,t ACG available frequency modulation capacity of its declaration must not be exceeded +.>Time period tMaterial represented by (24)The output of source i in the spot market +.>Sum of bid-winning capacities C in FM auxiliary services market i,t Must be at its own lower limit of force P i min And an upper limit P i max Within the range; formula (25) shows that in any response, a specific resource can be in either up-or down-regulated state,/or>And->The upper frequency modulation or lower frequency modulation zone bit of the resource i in the j-th response frequency modulation instruction signal is a 0-1 variable, the value of 1 represents that the resource i operates in the corresponding frequency modulation state, and the resource i does not operate in the corresponding frequency modulation state when the resource i is 0; equation (26) is the SOC constraint of the stored energy, S soc,t SOC, k for time period t down And k up The lower limit and the upper limit of the SOC are respectively; equation (27) is climbing constraint of frequency modulation resource, P i,t And P i,t-1 The sum of the output of the time period t and the t-1 resource i in the energy market and the frequency modulation auxiliary service market is delta P i The output force for resource i to allow to rise and fall in a period of time can be determined by querying the climbing rate of different types of resources.
Step three: and calling CPLEX technology to solve. The CPLEX technique is a mathematical optimization technique, which can express complex business problems as a mathematical programming model and solve the problems, and is used for improving efficiency, realizing strategies rapidly and improving yield.
Step four: solving a participation market dispatching strategy considering the energy storage life cycle. The participation market scheduling strategy taking into account the energy storage full life cycle includes the amount of participation of the energy storage in the spot market and the frequency modulation market at each moment in time, and the charge and discharge schedule.
The invention relates to an energy storage participation market scheduling optimization method considering the total life cycle cost, and the main content is divided into the construction of energy storage power station cost, energy storage power station income and objective function. In the aspect of energy storage power station cost measurement, considering the whole life cycle of the energy storage power station, and calculating the theoretical construction cost of the energy storage power station in the life cycle through the discount rate; in the aspect of energy storage power station income, energy storage is mainly considered to participate in spot market income and frequency modulation market income, and the spot market income comprises the spread benefit of high-price release of electric energy in low-price storage, the clean energy electric quantity benefit and the benefit brought by deferring equipment investment on the power grid side; frequency modulation market income is characterized in that the comprehensive performance indexes of response time, adjusting speed and peak clipping and valley filling effect indexes are firstly provided due to different types of energy storage power stations, so as to describe mileage income and capacity income of different types of energy storage power stations. In the aspect of objective function construction, the method aims at maximizing energy storage income, determines energy storage to participate in an electric energy market and auxiliary service market operation scheduling strategy, and provides a certain suggestion for energy storage power stations in China to participate in market trading strategy.
Example 2
As shown in fig. 4, the difference between the present embodiment and embodiment 1 is that the present embodiment provides an energy storage participation market schedule optimizing apparatus that accounts for the full life cycle cost, which uses the energy storage participation market schedule optimizing method of embodiment 1 that accounts for the full life cycle cost; the device comprises:
the energy storage participation market transaction scheduling structure construction unit is used for dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously constructing the energy storage participation market transaction scheduling structure description by combining the existing energy storage power station participation spot market and frequency modulation market mechanism;
the energy storage participation spot market measuring and calculating unit is used for constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
the energy storage participation frequency modulation market measuring and calculating unit is used for constructing comprehensive indexes according to the indexes of different energy storage power station characteristics, response time, adjustment speed and peak clipping and valley filling effects; the comprehensive index is used as the profit of dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model of the energy storage to participate in the frequency modulation market is obtained;
the energy storage power station full life cycle cost analysis unit is used for constructing an energy storage power station construction cost analysis model according to the energy storage power station full life cycle cost;
the scheduling strategy model determining unit is used for determining a scheduling strategy model considering the whole life cycle of the energy storage based on the fact that the energy storage participates in the operation of the electric energy market and the auxiliary service market and aims at maximizing the income;
and the scheduling strategy solving unit is used for solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
The execution process of each unit is performed according to the flow steps of the energy storage participation market dispatching optimization method of the embodiment 1, which takes the total life cycle cost into account, and the detailed description is omitted in this embodiment.
The invention also provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the energy storage participation market dispatching optimization method considering the whole life cycle cost when executing the computer program.
Meanwhile, the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the energy storage participation market dispatching optimization method considering the full life cycle cost when being executed by a processor.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The energy storage participation market scheduling optimization method considering the total life cycle cost is characterized by comprising the following steps of:
dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously combining the existing energy storage power station to participate in spot market and frequency modulation market mechanisms to construct the energy storage participation market transaction scheduling structure description;
constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
constructing comprehensive indexes according to the characteristics of different energy storage power stations, the response time, the adjustment speed and the peak clipping and valley filling effect indexes; the comprehensive index is used as the profit for dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model for the energy storage to participate in the frequency modulation market is obtained;
constructing an energy storage power station construction cost analysis model according to the total life cycle cost of the energy storage power station;
determining a scheduling strategy model considering the whole life cycle of the energy storage based on the energy storage participating in the operation of the electric energy market and the auxiliary service market and aiming at maximizing the income;
and solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
2. The energy storage participation market scheduling optimization method considering the full life cycle cost according to claim 1, wherein the expression of the comprehensive index is: the expression of the comprehensive index is:
wherein K is i For the comprehensive frequency modulation performance index epsilon of the frequency modulation resource in the ith scheduling period 1 Is thatWeight coefficient, epsilon 2 Is->Weight coefficient, epsilon 3 Is->Weight coefficient of (2); />The response time of the frequency modulation resource in the ith scheduling period is given, and k is the total number of frequency modulation instructions sent in the ith scheduling period; t is t i,j Responding the time of the j-th frequency modulation instruction in the i-th scheduling period for the frequency modulation resource; />For the adjustment speed, v, of the frequency modulation resource in the ith scheduling period sta Standard tuning speeds given for the frequency modulation market; />The actual regulation speed of the frequency modulation resource in response to the jth frequency modulation instruction in the ith scheduling period; />For the adjustment accuracy of the FM resource in the ith scheduling period,/th scheduling period>And->And respectively responding the required output and the actual output of the j-th frequency modulation instruction in the i-th scheduling period for the frequency modulation resource.
3. The energy storage participation market scheduling optimization method considering the full life cycle cost according to claim 1, wherein the direct benefit index refers to the benefit directly generated after the energy storage system is put into operation, including the difference benefit of high-price release of electric energy in low-price storage, the clean energy electric quantity benefit and the subsidy benefit;
the indirect benefit index refers to benefits brought by delaying equipment investment on the power grid side through configuration of a pure condensation system.
4. The energy storage participation market scheduling optimization method considering full life cycle costs according to claim 1, wherein the scheduling policy model is:
wherein t is a time point sequence number; n is a annual scheduling period; r is R cap Representing daily capacity gain, R mil Representing the daily mileage gain; r is R total Representing total income of the energy storage power station in the spot market; c is the full life cycle cost of the energy storage power station.
5. The energy storage participation market scheduling optimization method accounting for full life cycle costs of claim 4, wherein solving the scheduling policy model using CPLEX technique comprises:
inputting initial data to the scheduling strategy model, wherein the initial data comprises the life cycle of the energy storage power station, construction cost parameters, transaction parameters and discount rate;
considering the cost of the energy storage whole life cycle, the total earnings of spot and frequency modulation markets, taking the maximized earnings as an objective function, and constructing constraint conditions for the scheduling strategy model;
and solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
6. The energy storage participation market scheduling optimization method of claim 5, wherein the energy storage full life cycle participation market scheduling strategy includes the amount of participation in the spot market and the frequency modulated market at each time of energy storage, and a charge and discharge schedule.
7. The energy storage participation market schedule optimization method of claim 5, wherein the constraints include:
k down ≤S soc,t ≤k up (26)
-ΔP i ≤P i,t -P i,t-1 ≤ΔP i (27)
wherein, the formula (21) and the formula (22) are respectively the constraint of the system frequency modulation capacity requirement and the mileage requirement,and->Respectively representing the system leveling capacity requirement and the mileage requirement which are required to be met in the period t; equation (23) represents the winning capacity C in ACG of time period t resource i i,t ACG available frequency modulation capacity of its declaration must not be exceeded +.>Formula (24) shows the output of time period t resource i in the spot market +.>Sum of bid-winning capacities C in FM auxiliary services market i,t Must be at its own lower limit of force P i min And an upper limit P i max Within the range; formula (25) shows that in any response, a resource can be in one of up-or down-frequency modulation, and +_>And->The upper frequency modulation or lower frequency modulation zone bit of the resource i in the j-th response frequency modulation instruction signal is a 0-1 variable, the value of 1 represents that the resource i operates in the corresponding frequency modulation state, and the resource i does not operate in the corresponding frequency modulation state when the resource i is 0; equation (26) is the SOC constraint of the stored energy, S soc,t SOC, k for time period t down And k up The lower limit and the upper limit of the SOC are respectively; equation (27) is climbing constraint of frequency modulation resource, P i,t And P i,t-1 The sum of the output of the time period t and the t-1 resource i in the energy market and the frequency modulation auxiliary service market is delta P i The output force for allowing the resource i to rise and fall in a period of time is determined by inquiring the climbing rate of different types of resources.
8. An energy storage participation market scheduling optimization device taking full life cycle cost into account, characterized in that the device uses the energy storage participation market scheduling optimization method taking full life cycle cost into account as defined in any one of claims 1 to 7; the device comprises:
the energy storage participation market transaction scheduling structure construction unit is used for dividing the construction cost of the energy storage power station into service years of the energy storage power station, and simultaneously constructing the energy storage participation market transaction scheduling structure description by combining the existing energy storage power station participation spot market and frequency modulation market mechanism;
the energy storage participation spot market measuring and calculating unit is used for constructing a profit measuring and calculating model of the energy storage participation spot market according to the direct benefit index and the indirect benefit index of the energy storage participation spot market;
the energy storage participation frequency modulation market measuring and calculating unit is used for constructing comprehensive indexes according to the indexes of different energy storage power station characteristics, response time, adjustment speed and peak clipping and valley filling effects; the comprehensive index is used as the profit for dividing the energy storage to participate in the frequency modulation market, and a profit measuring and calculating model for the energy storage to participate in the frequency modulation market is obtained;
the energy storage power station full life cycle cost analysis unit is used for constructing an energy storage power station construction cost analysis model according to the energy storage power station full life cycle cost;
the scheduling strategy model determining unit is used for determining a scheduling strategy model considering the whole life cycle of the energy storage based on the fact that the energy storage participates in the operation of the electric energy market and the auxiliary service market and aims at maximizing the income;
and the scheduling strategy solving unit is used for solving the scheduling strategy model by adopting a CPLEX technology to obtain a participating market scheduling strategy considering the energy storage life cycle.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the energy storage participation market schedule optimization method of any one of claims 1 to 7 that accounts for full life cycle costs when executing the computer program.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the energy storage participation market schedule optimization method of any one of claims 1 to 7 accounting for full life cycle costs.
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