CN115207972A - Power supply planning method with coordinated capacity electricity price and wind, light and fire ratio - Google Patents
Power supply planning method with coordinated capacity electricity price and wind, light and fire ratio Download PDFInfo
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
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Abstract
The invention provides a power supply planning method for coordinating capacity electricity price and wind, light and fire ratio, which comprises the following steps: the method comprises the steps of planning power supplies to be thermal power, wind power and photovoltaic, considering a capacity compensation mechanism of a thermal power generating unit, and establishing a double-layer power supply planning model with capacity electricity price and wind-solar-fire ratio coordinated, wherein the double-layer power supply planning model comprises an upper-layer investment planning model and a lower-layer optimized operation model; the investment planning model on the upper layer takes the capacity compensation electricity prices of various power supplies and thermal power generating units as a planning main body, and performs power supply investment decision based on the minimum total cost and ensures the profits of various units; the optimization operation model of the lower layer carries out optimization operation simulation based on the target of the minimum annual operation cost; and solving the double-layer power supply planning model by adopting a genetic algorithm and a mixed integer planning method. The method can realize the coordinated planning of the power supply and the capacity electricity price, effectively guarantee the income of each unit while ensuring the economy of the system, and provide reference for the coordinated development of the future power system planning and market mechanism.
Description
Technical Field
The invention belongs to the field of power system planning, and particularly relates to a power supply planning method with coordinated capacity electricity price and wind, light and fire ratio.
Background
Under the drive of low-carbon energy strategy, the proportion of renewable energy is gradually increased, and the output randomness of the renewable energy makes the safe and stable operation of the power system face challenges. The thermal power generating unit is the most economical frequency modulation and peak regulation resource at present due to the characteristics of strong stability, high flexibility and the like, and the role of the thermal power generating unit is gradually transformed from a power generation power supply to a regulation power supply. However, with the change of roles of thermal power, a single electric quantity market can only ensure the recovery of the marginal operation cost of the thermal power unit, cannot embody the capacity value of the thermal power unit as a regulated power supply, and is not beneficial to the healthy development of the thermal power unit. How to give consideration to the capacity gain of the thermal power generating unit while planning the power supply structure has important significance for supporting the development of low-carbon energy and ensuring the safety and stability of an energy system.
In order to guarantee the long-term capacity abundance of the power system and provide effective power generation investment signals, a reasonable capacity compensation mechanism is adopted and is the future development direction. The capacity compensation mechanism relatively decouples the capacity cost recovery and the power generation operation of the unit [1], and a part of income is locked in advance for unit investment. The literature [2-6] system introduces and compares the existing capacity compensation mechanisms abroad, mainly comprises a scarce electricity price mechanism, a capacity subsidy mechanism and a capacity market mechanism, proves the necessity of the capacity compensation mechanism, provides an implementation route and a specific scheme for constructing the domestic capacity compensation mechanism, and lays a foundation for making the capacity electricity price. In the research, the method is only limited to a capacity compensation mechanism, and the survival problem of the thermal power generating unit caused by the change of the power supply structure is not comprehensively considered. With the acceleration of the energy transformation process, large-area loss of thermal power enterprises represented by coal and electricity has gradually become one of the main problems concerned by researchers. In the literature [7], a capacity compensation mechanism based on installed capacity is established aiming at the scale of the thermal power generating unit in the current situation, and a double-layer decision model of the thermal power generating unit considering the capacity compensation is established, and the calculation shows that the appropriate capacity compensation can ensure that the expected profit of the thermal power generating unit is positive, and the optimal capacity compensation price is in an increasing trend along with the continuous improvement of the permeability of renewable energy sources. The research aims at the current situation of the power supply, a planning power supply with continuously changed wind-light ratio in the future is not considered, and the unit capacity electricity price of the thermoelectric generator set is set in advance by the government in the research, is fixed and unchanged in the planning stage, and cannot reflect the mutual influence of the unit capacity electricity price and the power supply structure. Therefore, the invention provides a power supply planning method for coordinating capacity electricity price and wind, light and fire ratio.
Reference to the literature
[1] Wang Xiaoang, zhongpeng, ren Yuan, zhao xing quan, li Ming Dy, wang Qin, li hongjie, chang Wei, shanxi electric power spot market long-term on-stock connection problem and countermeasure [ J ] power grid technology, 2022,46 (01): 20-27.
[2] Chenda Yu, international practical comparative analysis of the matching capacity mechanism of the electric power spot market [ J ]. China electric power enterprise management, 2020 (01): 30-35.
[3] Wangyi, billow, zhangyuxin, lon, chenxinyu, wenjiu, a capacity compensation mechanism adapted to the development of the China electric power spot market was initially explored [ J ]. The automation of electric power systems, 2021,45 (06): 52-61.
[4] A method for evaluating the abundance of generating capacity in power market and its guarantee mechanism [ J ] is the automation of power system, 2020,44 (18): 55-63.
[5] Liu Shuo, in Songtai, sunday, spongelian, dongliang, qin and Yao, research on a capacity compensation mechanism of a high-proportion renewable energy power system [ J/OL ] power grid technology: 1-11[2022-05-09]. DOI:10.13335/j.1000-3673.Pst.2021.2117.
[6] Billow, picnic, zhaojing, korean, wangpeau, which 2815638, rainnuts, analysis of capacity guarantee mechanism of electric power market for development of high-proportion new energy [ J ] electric power construction, 2021,42 (03): 117-125.
[7] Wuzhaoyuan, zhongming, wangzaghuang, xiahing, li heptyinsyin, stimulated fire power provides flexible capacity compensation mechanism design [ J ] power system automation, 2021,45 (06): 43-51.
Disclosure of Invention
Aiming at the problems, the invention provides a power supply planning method with capacity electricity price and wind-solar-fire ratio coordinated, which takes the capacity compensation of a thermal power generating unit into consideration in the construction of a future high-proportion new energy power system as a research scene, and comprises the following steps: the method comprises the steps that a planning power supply is thermal power, wind power and photovoltaic, a capacity compensation mechanism of a thermal power unit is considered, a double-layer power supply planning model with capacity electricity price and wind-solar-fire ratio coordinated is established, and the double-layer power supply planning model comprises an upper-layer investment planning model and a lower-layer optimized operation model; the investment planning model of the upper layer takes the capacity compensation electricity prices of various power supplies and thermal power generating units as a planning main body, and performs power supply investment decision based on the minimum total cost and ensures the profits of various units; the lower-layer optimized operation model carries out optimized operation simulation based on the objective of minimum annual operation cost; and solving the double-layer power supply planning model by adopting a genetic algorithm and a mixed integer planning method.
The solving of the model comprises:
initializing unit scheduling output and start-stop plans in typical days of spring, autumn, summer and winter, generating an upper power supply investment planning initial scheme through a genetic algorithm, and transmitting the upper power supply investment planning initial scheme to a lower operation model;
the lower-layer operation model decides scheduling output and start-stop plans of each unit in spring, autumn, summer and winter typical days respectively according to the power supply investment planning scheme of the upper layer, and returns the lower-layer operation result to the upper-layer model;
the upper layer investment planning model obtains new unit dispatching output and starting and stopping plans in each typical day, the new unit dispatching output and starting and stopping plans are solved again through a genetic algorithm, a new power supply investment planning scheme is obtained, and the new power supply investment planning scheme is transmitted to the lower layer operation model;
and repeating the steps until the upper-layer and lower-layer iterations reach the maximum times, exiting the cycle, and outputting the optimal power supply planning result and the operation scheme.
The objective function of the power supply investment planning model at the upper layer is as follows:
minF 1 ＝f inv +f fix +f ope +f gre +f cap
wherein, F 1 To plan the horizontal annual total cost, f inv Investment cost f for newly built unit fix For the annual fixed maintenance cost, f of the unit ope For the annual operating cost of the system, f gre Quota cost, f for system renewable energy cap The cost is compensated for the capacity; the constraint conditions comprise electric power constraint, installed scale constraint, unit annual net profit constraint and capacity electricity price constraint.
The objective function of the lower optimization operation model is as follows:
minF 2 ＝f o +f ren +f car
wherein, F 2 For daily operating cost, f o For daily operating costs including unit operating costs, f ren Penalty cost, f, for electricity abandonment of renewable energy sources car Cost for carbon emissions; the constraint conditions comprise power balance constraint, operation constraint of various types of units, climbing constraint of the units and start-stop time constraint.
The invention has the beneficial effects that: the invention provides a capacity compensation mechanism of a thermal power generating unit based on effective capacity, which is suitable for China, by analyzing the current capacity compensation mechanisms at home and abroad, makes clear the application scenes of various capacity compensation mechanisms and combining the actual construction situation of the electric power market in China, and has guiding significance for the cost recovery of the thermal power generating unit under a high-proportion new energy electric power system in the future. Meanwhile, a double-layer power supply planning model which considers the coordination of the capacity electricity price of thermal power capacity compensation and the wind-solar-fire ratio is established based on a thermal power unit capacity compensation mechanism, the model can realize the coordination planning of the power supply and the capacity electricity price, the economic efficiency of the system is guaranteed, the income of each unit is effectively guaranteed, and reference is provided for the future power system planning and the coordination development of a market mechanism.
Drawings
FIG. 1 is a structure of a capacity compensation mechanism of a thermal power generating unit in the present invention;
FIG. 2 is an overall framework of the power supply planning two-layer model of the present invention;
fig. 3 is a flow chart of solving the power planning two-layer model in the present invention.
Detailed Description
The embodiments are described in detail below with reference to the accompanying drawings.
Under the "dual carbon" target background, many measures have been proposed in the power industry to encourage renewable energy development and reduce system carbon emissions. According to the invention, carbon tax and a renewable energy quota system are considered when power supply planning is carried out, and the carbon emission and the renewable energy consumption in the system operation process are quantized into the system power generation cost by using the price signal, so that the initiative of each main body is mobilized, and the system power supply configuration is guided to develop towards clean energy.
The carbon tax is used for pricing the carbon emission of the thermal power generating unit in a tax mode, and as the thermal power generating unit is the most main carbon source, the carbon emission cost of the system, namely the carbon emission cost of the thermal power generating unit, is calculated according to the following formula:
f i car ＝γ car e i P i (1)
in the formula: gamma ray car Represents a carbon tax; e.g. of the type i Representing the carbon emission coefficient of the thermal power generating unit i; p i And the power generation amount of the thermal power generating unit i is represented.
The green certificate transaction mechanism is used as a matching system of a renewable energy quota system, the renewable energy power generation amount is quantized, and when the distribution and sale company does not complete the quota requirement specified by the government, the quota requirement can be completed in a mode of purchasing green certificates from other assessment subjects. The renewable energy quota cost of the whole system is considered, when the renewable energy generating capacity of the system does not meet the system quota requirement, green certificates need to be purchased to pay the renewable energy quota cost, and meanwhile, when the renewable energy generating capacity of the system is higher than the system quota requirement, the green certificates can be sold to obtain the renewable energy quota income, and the renewable energy quota cost f gre As follows:
f gre ＝γ gre k(δ gre P all -P ren ) (2)
in the formula: gamma ray gre Represents a green certificate transaction price; k represents a quantization coefficient, the renewable energy quota is quantized to the number of green certificates, and k =1 book/MW · h; delta gre Representing a renewable energy quota coefficient; p all Representing the sum of the system power generation; p ren Representing the sum of the renewable energy power generation of the system.
At present, capacity compensation mechanisms at home and abroad mainly can be divided into three categories, namely a capacity market mechanism, a scarce pricing mechanism in a pure energy market and a capacity subsidy mechanism. The capacity market mechanism puts higher requirements on the accuracy of a capacity demand curve, china is in the economic high-speed development period, most provincial and urban electric loads are difficult to predict accurately, and in addition, the capacity market needs to be coordinated with a perfect electric energy market, so that China does not have the condition of building the capacity market at present; the scarce pricing mechanism can only reflect short-term supply-demand relation, so that the electricity price fluctuates, high risk exists in long-term power generation investment, and the current market information in China is not disclosed enough, so that whether the scarce electricity price appears reasonably can not be distinguished, and the method is not suitable for the current market development situation in China; the capacity subsidy mechanism is simple and easy to implement, is suitable for the initial development stage of the power market, and is applied to Shandong, guangdong and other provinces in China. Therefore, the invention selects a capacity subsidy mechanism which is suitable for the current development situation of China to carry out capacity compensation design and aims at the representative thermal power generating unit. And the recovery of the cost of the generating capacity of the thermal power generating unit is realized by accounting the capacity electricity price and the compensation capacity of the thermal power generating unit. The structure of the capacity compensation mechanism is shown in fig. 1.
1) Capacity electricity price
The unit capacity electricity price is calculated based on the fixed cost of the unit capacity of the thermal power generating unit. The investment cost depreciation fee is a main component of the fixed cost, and the rest cost is related to the unit operation efficiency. Therefore, the invention mainly considers the depreciation cost of the investment cost of the thermal power generating unit as the accounting basis of the capacity electricity price. The following formula is the unit capacity electrovalence lambda of thermal power cap Pricing range of (c):
in the formula: k g,inv Investment cost of unit capacity of the thermal power generating unit; sigma is the showing rate, and is generally 7%; n is a radical of i The service life of the unit is generally 30 years.
2) Compensating capacity
The compensation capacity in the capacity compensation mechanism is calculated based on the effective capacity of the unit. Firstly, the unit availability factor, the plant power consumption rate, the maintenance time ratio and the forced outage rate are considered to calculate the unit availability factor. In addition, because the depreciation cost difference of the units with different production years is large, the production year correction coefficient is calculated according to the production year of the units, and the product of the installed capacity of the units, the available coefficient and the production year correction coefficient is used as the compensatable capacity of each unit.
Adjusting the installed capacity of the thermal power generating unit by considering the fuel availability ratio, the plant power consumption rate and the annual overhaul plan of the unit to obtain the initial effective capacity of the unit
In the formula:
the installed capacity of the thermal power generating unit i; f i 1 The fuel availability ratio of the thermal power generating unit i is obtained; f i 2 The service power coefficient of the thermal power generating unit i is obtained; f i 3 And the proportion of the annual overhaul maintenance time of the thermal power generating unit i is increased.
On the basis of the primary effective capacity of the unit, a multi-state unit probability model is adopted to consider the forced outage rate of the unit, and the effective capacity of the unit is obtained
In the formula: epsilon i And the unit is the equivalent forced outage rate of the unit i.
Finally, the effective capacity of the unit is corrected according to the unit production time limit to obtain the compensation capacity of each unit
In the formula: f i 4 And (4) for correcting the coefficient of the operating age of the thermal power generating unit i, taking 1 for the newly-built unit, and converting the original old unit according to the operating age.
3) Settlement mode
Based on the investment cost of the unit, the upper limit of the capacity electricity price compensation of the unit can be determined; based on the installed capacity of each unit, the compensable capacity of the unit can be determined after correction; the capacity compensation fee is collected from the user side and is settled monthly. The total income of the thermal power generating unit is equal to the sum of the electric quantity income and the capacity income of the thermal power generating unit. The capacity compensation income obtained by the thermal power generating unit i is f i cap ：
The power supply planning problem, which is coordinated with the capacity price, has a two-layer structure. The method mainly plans power supplies to be thermal power, wind power and photovoltaic, an upper model takes various power supplies and capacity compensation electricity prices of thermal power generating units as a planning main body, power supply investment decision is made on the basis of minimum total cost, and profits of various units are guaranteed; the lower model performs optimization operation simulation based on the objective of minimum annual operation cost. The overall framework of the power planning two-layer model is shown in fig. 2.
Upper power investment planning model to plan horizontal annual total cost F 1 Minimum target, total cost including new unit investment cost f inv Annual fixed maintenance cost f of unit fix Annual system running cost f ope System renewable energy quota cost f gre And a capacity compensation charge f cap . The decision variable is a scheme for newly building the unit, including whether the thermal power unit i to be selected is put into operation with alpha i Whether the wind turbine generator j to be selected is put into operation with alpha j Whether the photovoltaic unit k to be selected is put into operation alpha or not k And unit capacity electricity price compensation variable lambda of thermal power generating unit cap . The objective function may be specifically expressed as:
min F 1 ＝f inv +f fix +f ope +f gre +f cap (8)
1) Investment cost of newly-built unit
In the formula: phi g,new 、Φ w,new 、Φ pv,new Respectively represents the newly built thermal power wind power and photovoltaic unit set, phi g,old Representing the existing thermal power generating unit set; CRF denotes the capital recovery factor; k g,inv 、K w,inv 、K pv,inv Respectively representing the unit capacity investment cost of newly built thermal power generating units, wind power generating units and photovoltaic units;
representing the capacities of a thermal power generating unit i, a wind power generating unit j and a photovoltaic unit k; n is a radical of i 、N j 、N k Respectively representing the service life of each unit; alpha is alpha i 、α j 、α k Is a variable of 0 to 1, respectively represents the states of a thermal power unit i, a wind power unit j and a photovoltaic unit k, and alpha is the state of the existing thermal power unit, wind power unit and photovoltaic unit i,j,k =1 for thermal power generating unit to be selected and renewable energy generating unit, alpha i,j,k =0 for not commissioning, α i,j,k And =1 represents the commissioning.
2) Annual fixed maintenance cost of unit
In the formula: phi g 、Φ w 、Φ pv Respectively representing all thermal power generating units and wind power photovoltaic unit sets; k g,fix 、K w,fix 、K pv ,fix And the fixed maintenance cost of the thermal power generating unit, the wind power generating unit and the photovoltaic unit in unit capacity is represented.
3) Annual operating cost of the system
And selecting 3 typical days of spring, autumn, summer and winter to optimize operation due to different load characteristics in different seasons. Specifically, it can be expressed as:
in the formula: s represents a typical day within an equivalent horizontal year; f 2,s The daily operation cost of a typical day s is obtained by the lower-layer optimized operation, namely a lower-layer objective function; theta s Days of typical days s.
4) System renewable energy quota cost
In the formula: p i,s,t 、P j,s,t 、P k,s,t And the power generation amounts of the thermal power generating unit i, the wind power generating unit j and the photovoltaic power generating unit k at the s-th typical day t moment are respectively represented.
5) Cost of capacity compensation
In the formula: lambda [ alpha ] cap Representing the unit capacity compensation electricity price of the thermal power generating unit i;
and representing the compensation capacity of the thermal power generating unit i.
The constraints are as follows:
1) Electric power constraint
In the formula: x is the number of w 、x pv Respectively is the confidence capacity coefficient of the wind and light machine set; p d,max Is the annual maximum load; r d Indicating the capacity spare factor.
2) Installed scale constraint
In the formula: c g,max 、C w,max 、C pv,max Respectively showing the maximum installed scale of thermal power, wind power and photovoltaic units.
3) Annual net profit constraint for a unit
In the formula: n is a radical of i 、N j 、N k Respectively representing net profits of the thermal power generating unit i, the wind power generating unit j and the photovoltaic unit k in an equivalent horizontal year; lambda [ alpha ] g 、λ w 、λ pv And the grid-connected electricity prices of the thermal power generating unit, the wind power generating unit and the photovoltaic unit are respectively represented.
In addition to the power constraint, the installed scale constraint and the annual profit constraint of the unit, the upper model constraint also includes a capacity electricity price constraint, see equation (3).
And the lower-layer optimized operation model optimizes the output and start and stop of each unit by taking the lowest daily operation cost as an objective function. Daily operating costs include unit operating costs f o And the penalty cost f of electricity abandonment of renewable energy sources ren Carbon emission cost f car And the decision variable is the generating capacity of the unit in each time period in a typical day. The objective function may be specifically expressed as:
minF 2 ＝f o +f ren +f car (22)
1) Operating costs of the units
In the formula: t represents each operating period in a typical day, T =24; c g,ope 、C w,ope 、C pv,ope Respectively representing the unit operation cost of a thermal power generating unit, a wind power generating unit and a photovoltaic unit; u. of i,t Representing the starting and stopping conditions of the thermal power generating unit i at the time t, and taking u as a variable of 0-1 i,t =0 for shutdown, u i,t =1 stands for boot;
the starting cost of the thermal power generating unit i is shown, and the stopping cost is ignored; p i,t 、P j,t 、P k,t And the generated energy of the thermal power generating unit i, the wind power generating unit j and the photovoltaic power generating unit k at the moment t is respectively represented.
2) Penalty cost of electricity abandonment of renewable energy
In the formula: rho pun Representing the punishment cost of the renewable energy power abandoning unit;
and respectively representing the predicted output of the wind turbine j and the photovoltaic turbine k in the time period t.
3) Cost of carbon emissions
The constraints are as follows:
1) Power balance constraint
In the formula: p t d Representing the amount of load during the t period.
2) Operating constraints for various types of units
In the formula: p is i g,min 、P i g,max And respectively representing the minimum and maximum output coefficients of the thermal power generating unit i.
3) Unit climbing restraint
P i- ≤P i,t -P i,t-1 ≤P i+ (30)
In the formula: p i- 、P i+ The downward climbing speed and the upward climbing speed of the thermal power generating unit i are respectively represented.
4) Start-stop time constraint
In the formula (I), the compound is shown in the specification,
the minimum start-up and shut-down time allowed by the thermal power generating unit i are respectively.
The power supply planning model with the coordinated capacity electricity price and the wind, light and fire ratio has a double-layer structure, the upper layer and the lower layer have different decision variables and decision targets, but the decisions of the layers are correlated and restricted, namely the decision variables of the upper layer are transmitted to the lower layer model as parameters, and the result of the decision variables of the lower layer influences the optimal value of the objective function of the upper layer. The upper layer takes the minimum total cost as a target, takes the newly-built capacity and the capacity electricity price of each unit as decision variables, and transmits the newly-built capacity of the unit to the lower layer. The lower layer performs operation simulation by taking the minimum annual operation cost as a target, takes the typical daily operation output of each unit as a decision variable, and transmits the daily operation output of the unit to the upper layer. The upper layer has a decision variable product term which is a mixed integer nonlinear programming model and is solved by adopting a genetic algorithm. And then solving a lower-layer mixed integer linear programming model by adopting a CPLEX solver based on a YALMIP platform. The solving flow is shown in fig. 3.
The method comprises the following specific steps:
1) Inputting basic parameters such as a wind-light fire engine set and the like, selecting three typical days of spring and autumn, summer and winter, and inputting typical day load and wind-light predicted output data;
2) Setting the initial iteration times G of the upper and lower layer models as 0;
3) Setting the initial iteration times K of the upper layer model as 0;
4) Initializing power generation scheduling arrangement of each typical day-down unit;
5) According to the unit power generation scheduling arrangement, the upper layer model decides a power supply planning scheme according to the formula (1) and the formulas (8) to (21);
6) Judging whether the upper layer model reaches the maximum iteration times, if not, performing variation, crossing and selection operations on the population, and repeating the step 5 after the iteration times are K + 1); if so, outputting an optimal power supply planning scheme of the upper model;
7) Judging whether the upper-layer model and the lower-layer model reach the maximum iteration times, if not, transmitting the upper-layer power supply planning scheme to the lower layer, G +1, calling CPLEX to solve the lower-layer model according to the upper-layer power supply planning scheme and the formulas (22) to (32), obtaining the optimal power supply operation scheme under the power supply planning scheme, and transmitting the optimal power supply operation scheme to the upper layer; if so, outputting a final planning result and an operation scheme;
8) And repeating the steps 5) to 7) until a final planning result is output.
The present invention is not limited to the above embodiments, and any modifications or alterations that can be easily conceived by those skilled in the art within the technical scope of the present invention are intended to be covered by the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A power supply planning method for coordinating capacity electricity price and wind-solar-fire ratio comprises the following steps: the method comprises the steps that a planning power supply is thermal power, wind power and photovoltaic, a capacity compensation mechanism of a thermal power unit is considered, a double-layer power supply planning model with capacity electricity price and wind-solar-fire ratio coordinated is established, and the double-layer power supply planning model comprises an upper-layer investment planning model and a lower-layer optimized operation model; the investment planning model of the upper layer takes the capacity compensation electricity prices of various power supplies and thermal power generating units as a planning main body, and performs power supply investment decision based on the minimum total cost and ensures the profits of various units; the lower-layer optimized operation model carries out optimized operation simulation based on the objective of minimum annual operation cost; and solving the double-layer power supply planning model by adopting a genetic algorithm and a mixed integer planning method.
2. The power supply planning method based on coordination between capacity electricity price and wind, solar and fire ratio according to claim 1, wherein the solution process of the double-layer model is as follows:
step 1) inputting basic parameters of a wind-solar fire unit, selecting three typical days of spring and autumn, summer and winter, and inputting typical daily load and wind-solar predicted output data;
step 2) setting the initial iteration times G of the upper layer model and the lower layer model as 0;
step 3) setting the initial iteration times K of the upper layer model as 0;
step 4) initializing the power generation scheduling arrangement of the unit under each typical day;
step 5) deciding a power supply planning scheme according to the unit power generation scheduling arrangement, the objective function of the upper model and the constraint condition;
step 6) judging whether the upper layer model reaches the maximum iteration times, if not, performing variation, crossing and selection operations on the population, and repeating the step 5 if the iteration times are K + 1); if so, outputting an optimal power supply planning scheme of the upper model;
7) Judging whether the upper layer model and the lower layer model reach the maximum iteration times, if not, transmitting the upper layer power supply planning scheme to the lower layer, G +1, calling CPLEX to solve the lower layer model according to the upper layer power supply planning scheme, the lower layer model objective function and the constraint condition to obtain the optimal power supply operation scheme under the power supply planning scheme, and transmitting the optimal power supply operation scheme to the upper layer; if so, outputting a final planning result and an operation scheme;
8) And repeating the steps 5) to 7) until a final planning result is output.
3. The power supply planning method for coordinating capacity electricity price with wind, light and fire ratio according to claim 1 or 2, wherein the objective function of the power supply investment planning model of the upper layer is as follows:
minF 1 ＝f inv +f fix +f ope +f gre +f cap
wherein, F 1 To plan the horizontal annual total cost, f inv Investment cost f for newly built unit fix For the annual fixed maintenance cost, f of the unit ope For the annual operating cost of the system, f gre Quota cost, f for system renewable energy cap To compensate for the cost for the capacity;
in the formula phi g,new 、Φ w,new 、Φ pv,new Respectively represents the newly built thermal power wind power and photovoltaic unit set, phi g,old Representing the existing thermal power generating unit set; CRF denotes the capital recovery factor; k g,inv 、K w,inv 、K pv,inv Respectively representing the unit capacity investment cost of newly built thermal power generating units, wind power generating units and photovoltaic units;
representing the capacities of a thermal power generating unit i, a wind power generating unit j and a photovoltaic unit k; n is a radical of i 、N j 、N k Respectively showing the service life of each unit; alpha is alpha i 、α j 、α k Is a variable of 0 to 1, respectively represents the states of a thermal power unit i, a wind power unit j and a photovoltaic unit k, and alpha is the state of the existing thermal power unit, wind power unit and photovoltaic unit i,j,k =1 for thermal power generating unit to be selected and renewable energy generating unit, alpha i,j,k =0 for no investment, α i,j,k =1 represents commissioning;
in the formula phi g 、Φ w 、Φ pv Respectively representing all thermal power generating units and wind power photovoltaic unit sets; k g,fix 、K w,fix 、K pv,fix And the fixed maintenance cost of the thermal power generating unit, the wind power generating unit and the photovoltaic unit in unit capacity is represented.
Because the load characteristics are different in different seasons, the optimal operation is carried out by selecting 3 typical days in spring, autumn, summer and winter, which can be specifically expressed as:
wherein s represents a typical day within an equivalent horizontal year; f 2,s The daily operation cost of a typical day s is obtained by the optimized operation of a lower layer, namely a lower layer objective function; theta s Days typical of day s;
in the formula, P i,s,t 、P j,s,t 、P k,s,t Respectively representing the generated energy of a thermal power generating unit i, a wind power generating unit j and a photovoltaic power generating unit k at the s-th typical day t moment;
in the formula, λ cap Representing the unit capacity compensation electricity price of the thermal power generating unit i;
and representing the compensation capacity of the thermal power generating unit i.
4. The power supply planning method for coordinating capacity electricity price and wind, light and fire ratio according to claim 3, wherein the constraints of the power supply investment planning model of the upper layer comprise:
1) Electric power constraint
In the formula, x w 、x pv Respectively is the confidence capacity coefficient of the wind and light machine set; p d,max Is the annual maximum load; r d Representing a capacity reserve factor;
2) Installed scale constraint
In the formula, C g,max 、C w,max 、C pv,max Respectively representing the maximum installed scale of thermal power, wind power and photovoltaic units;
3) Annual net profit constraint for a unit
In the formula, N i 、N j 、N k Respectively representing net profits of the thermal power generating unit i, the wind power generating unit j and the photovoltaic unit k in an equivalent horizontal year; lambda [ alpha ] g 、λ w 、λ pv Respectively representing the grid-connected electricity prices of a thermal power generating unit, wind power generation and a photovoltaic unit;
4) Capacity price constraint
In the formula: lambda [ alpha ] cap The unit capacity electricity price of the thermal power generating unit is obtained; k g,inv Investment cost of unit capacity of the thermal power generating unit; sigma is the current rate, generally 7%; n is a radical of hydrogen i The service life of the unit is generally 30 years.
5. The power supply planning method for coordinating capacity electricity price and wind-solar-fire ratio according to claim 1 or 2, wherein the objective function of the lower-layer optimized operation model is as follows:
minF 2 ＝f o +f ren +f car
wherein, F 2 For daily operating cost, f o For daily operating costs including unit operating costs, f ren Penalty cost, f, for electricity abandonment of renewable energy sources car Cost for carbon emissions;
1) Operating costs of the units
Wherein T represents each operation period in a typical day, and T =24; c g,ope 、C w,ope 、C pv,ope Respectively representing the unit operation cost of a thermal power generating unit, a wind power generating unit and a photovoltaic unit; u. u i,t Representing the starting and stopping conditions of the thermal power generating unit i at t time period, wherein u is a variable of 0-1 i,t =0 for shutdown, u i,t =1 represents power on;
the starting cost of the thermal power generating unit i is shown, and the stopping cost is ignored; p i,t 、P j,t 、P k,t Respectively representing the generated energy of a thermal power generating unit i, a wind power generating unit j and a photovoltaic power generating unit k at the moment t;
2) Penalty cost of electricity abandonment of renewable energy
In the formula, ρ pun Representing the punishment cost of the renewable energy power abandoning unit;
respectively representing the predicted output of the wind turbine j and the photovoltaic turbine k in the time period t;
3) Cost of carbon emissions
6. The power supply planning method for coordinating capacity electricity price and wind, light and fire ratio according to claim 5, wherein the constraints of the lower-layer optimized operation model are as follows:
1) Power balance constraint
In the formula, P t d Representing the load amount of the t period;
2) Operating constraints for various types of units
u i,t α i P i g,min ≤P i,t ≤u i,t α i P i g,max
In the formula, P i g,min 、P i g,max Respectively representing the minimum and maximum output coefficients of the thermal power generating unit i;
3) Unit slope climbing restraint
P i- ≤P i,t -P i,t-1 ≤P i+
In the formula, P i- 、P i+ Respectively representing the downward climbing speed and the upward climbing speed of the thermal power generating unit i;
4) Start-stop time constraints
In the formula (I), the compound is shown in the specification,
the minimum start-up and shut-down time allowed by the thermal power generating unit i are respectively.
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