CN109149571A - A kind of energy storage Optimal Configuration Method of the combustion gas of consideration system and fired power generating unit characteristic - Google Patents
A kind of energy storage Optimal Configuration Method of the combustion gas of consideration system and fired power generating unit characteristic Download PDFInfo
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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
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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
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Abstract
The present invention relates to the energy storage Optimal Configuration Methods of a kind of consideration system combustion gas and fired power generating unit.This method: first according to historical data, predicting generation of electricity by new energy unit output, constructs generation of electricity by new energy unit output typical scene collection, in conjunction with load fluctuation characteristic, constructs power system load scene collection；Analyze the operation characteristic of Gas Generator Set and fired power generating unit start and stop stage, establish state transition equation group, clear state builds jump condition, establish the state transition model of the start and stop stage running of Gas Generator Set and fired power generating unit, transfer and switching during realization Gas Generator Set and fired power generating unit start and stop stage running between different conditions；According to system and operating parameter, on the basis of considering wind electricity digestion target, with correlative investment and the operation minimum target of total cost, building considers the energy storage Optimal Allocation Model of Gas Generator Set and fired power generating unit climbing capacity and the transfer of multistage state；Above-mentioned electric system energy storage optimization allocation is solved, electric system energy storage configuration scheme is obtained.
Description
Technical Field
The invention belongs to the technical field of power system planning, and particularly relates to an energy storage optimal configuration method considering characteristics of system gas and thermal power generating units.
Background
Environmental issues arising from extensive economic development models have caused renewable energy sources to be of great interest for their green environmental friendliness (e.g., wind energy). The access of large-scale clean energy tends to improve the environment and simultaneously brings new challenges to the operation of an electric power system, for example, the peak regulation pressure of the electric power system is increased day by day, the system peak regulation becomes one of new problems of the dispatching operation of the electric power system, and the insufficient peak regulation capability becomes a main factor for restricting the consumption capability of the clean energy. On one hand, the power grid needs to have a more flexible operation mode, and the regulation capacity of the power system is improved; on the other hand, the volatility and intermittency of the renewable energy sources need to be fully considered in the planning process of the power system (especially flexible resources including energy storage), so that the power grid has the capability of actively accessing the clean energy sources.
Compared with the traditional operation mode, the power system needs more standby resources to deal with the uncertainty caused by the new energy access. At present, whether each resource in the system has the capability of receiving a system standby scheduling instruction in the running process is not considered when the power system solves the standby optimization problem. In order to solve the above problems, the operation characteristics of each resource of the system (for example, the start-stop characteristic and the climbing characteristic of the unit need to be considered, the limitation on the SOC range needs to be considered for energy storage, etc.) need to be fully considered, and a more refined operation model is further proposed.
Based on the method, the operation characteristics and the climbing capacity of the gas and thermal power generating units in the starting and stopping stages are comprehensively considered, and the energy storage optimization configuration method considering the climbing capacity and the multi-stage state transfer of the system gas and thermal power generating units is provided.
Disclosure of Invention
The invention aims to provide an energy storage optimal configuration method considering characteristics of system gas and a thermal power unit, which can represent mutual switching and transferring relations between states of the gas power unit and the thermal power unit during operation, and can represent power tracks and operation characteristics of the thermal power unit under different starting types in a differentiated mode. The standby problem of power system operation is considered simultaneously, and the condition of comprehensively considering energy storage and unit to provide rotation standby for the system together more accords with the actual operation condition, more accords with the actual condition, and the practicality is stronger simultaneously.
In order to achieve the purpose, the technical scheme of the invention is as follows: an energy storage optimal configuration method considering characteristics of system gas and thermal power generating units comprises the following steps,
s1, firstly, predicting the output of the new energy generator set according to historical data, constructing a typical scene set of the output of the new energy generator set, and constructing a load scene set of the power system by combining with the load fluctuation characteristic;
s2, analyzing the operation characteristics of the gas generating unit and the thermal power generating unit in the start-stop stage, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the operation of the gas generating unit and the thermal power generating unit in the start-stop stage, and realizing the transfer and switching between different states in the operation process of the gas generating unit and the thermal power generating unit in the start-stop stage;
s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target;
s4: and solving the energy storage optimal configuration problem of the power system to obtain an energy storage optimal configuration scheme of the power system.
In an embodiment of the present invention, the step S1 is specifically implemented as follows:
uncertainty of wind power output and load mainly considers deviation of wind speed and load prediction, and respective deviation is considered to be normal load distribution; the actual values of the wind speed and the load can be represented after the predicted expected value and the predicted error; the form is as follows:
in the formula: v (t), PL(t) true values for wind speed and load, respectively;respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) wind speed and load prediction errors, respectively, both obeying probability distribution;
the wind power output can be calculated according to the following formula:
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed; v. ofinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
and combining the wind power output and the load generated by the simulation to generate a power system operation scene set.
In an embodiment of the present invention, the step S2 is specifically implemented as follows:
1) analyzing the operating characteristics of the thermal power generating unit in the starting and stopping stage: the starting and stopping processes of the thermal power generating unit need to go through the load increasing and load reducing processes;
2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring a 0-1 variable representing the state: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;indicating whether the unit i is in a load-up state at the moment t;indicating whether the unit n is in a scheduling receiving state at the moment t;indicating whether the unit n is in a load reduction state at the moment t;
3) defining the state establishing and transferring condition of the thermal power generating unit, and establishing a state transferring equation set: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, the following state transfer equation set is introduced to represent the switching of the thermal power generating unit among the operating states;
yi(t)-zi(t)＝ui(t) (5)
yi(t)+zi(t)≤1 (9)
the formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; the variables in the above formulae are all variables from 0 to 1, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;the variable is a variable for controlling the unit to enter and jump out of a schedulable state;the variable is used for controlling the unit to enter and jump out of the load reduction state;
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t; the formula (17) to the formula (18) show that the output of the thermal power generating unit just entering the schedulable state and the load reduction state must be equal toP iThe connection between the states of the thermal power generating unit is ensured, and the two states are noteworthyThe formula is only suitable for thermal power generating units and is not suitable for quick start-stop units including gas units;
Δpi(t)＝pi(t)-pi(t-1) (19)
the output variation delta p of the unit under the normal operation state of the systems of the formula (19) and the formula (21) respectivelyi(t) the amount of change in output when the upper spinning reserve is calledAnd the amount of change in output when the lower spinning reserve is calledWherein,andis the value of upper rotation standby and lower rotation standby provided by the unit;
4) writing a thermal power unit operation characteristic constraint equation in a column mode, and perfecting a thermal power unit start-stop stage model:
wherein, Rui(t) and Rdi(t) the climbing and descending capacities of the unit at the time t and can be calculated by the following formula;
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
wherein,andis the duration of the load up and load down;
equation (26) to equation (28) are respectively the maximum and minimum output of the time group when the upper spinning standby is called and the lower spinning standby is called in the normal running state of the system; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
wherein,andrespectively starting and stopping time;andrespectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) can be calculated from formula (31);
in an embodiment of the present invention, the step S3 is specifically implemented as follows:
1) an energy storage optimization configuration model objective function considering the climbing capacity and the multi-stage state transition of the gas power unit and the thermal power unit is constructed as follows:
in the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is an electric energy storage equipment set, and S belongs to S; e, wind power output scene set; generating cost, starting cost, stopping cost and standby service cost of the gas and thermal power generating unit i at the moment t are respectively set;investment costs for electrical energy storage devices;investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoad loss cost and unit wind abandon punishment cost for power system scheduling; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t can be calculated by the following formulas (33) -35; the investment reserve of the electric energy storage equipment and the transmission line can be calculated according to an equation (36) and an equation (37);
in the above formulas:respectively the no-load cost and the linear power generation cost of the unit i;respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs the capacity expansion requirement of line l;
2) the method comprises the following steps of constructing energy storage optimization configuration model constraint conditions considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit as follows:
2.1) Power System operating characteristic constraints
The power system operation characteristic constraints comprise power balance, direct current power flow constraint, transmission line capacity constraint and power system standby requirement constraint;
① the power balance constraint may be expressed in the form:
in the formula: n is a power system network topology node set;the node n is a set of the units;the wind generating set is a set of wind generating sets at the node n;is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;the scheduling value of the wind power plant j at the time t;respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
②, direct current power flow constraint, adopting a direct current power flow equation neglecting network loss, and the common expression of the direct current power flow model is as follows:
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the voltage phase angle difference of the system node n and the node k at the time t; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
③ the transmission line capacity constraint may be expressed in the form:
in the formula:maximum transmission capacity of a line connecting a system node n and a node k;
④ Power System backup requirement constraints the expressions of equations (41) and (42) apply to different types of backup requirements of the power system:
in the formula: pr (-) is a probability function;andrespectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;andα and β are confidence levels respectively meeting the upper backup and the lower backup of the system;
2.2) Electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48):
equations (43) - (48) are energy constraints of the electrical energy storage device; es(t) is the electric energy stored by the electric energy storage device s at the moment t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;the charge-discharge efficiency of the electrical energy storage device s, respectively; γ srespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;the maximum charging and discharging power of the electrical energy storage device s is respectively; the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; equation (48) is the charge-discharge balance constraint of the electrical energy storage device under consideration of self-discharge;
2.3) energy storage Standby service Capacity
The energy storage backup service capacity needs to satisfy the following constraints:
in the formula:andrespectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
2.4) wind generating set output restraint
The output of the wind generating set is restricted as follows:
in the formula:the output value of the wind power plant j at the moment t is obtained;
in an embodiment of the present invention, in step S4, the established energy storage optimization configuration method considering the climbing capability and the multi-stage state transition of the gas and thermal power generating units is linearized into a standard mixed integer linear programming model, and then the CPLEX is called by using the business software GAMS to facilitate the solution, so as to obtain the power system scheduling decision scheme.
Compared with the prior art, the invention has the following beneficial effects: the method provides a unified form, represents the mutual switching and transferring relation between the states of the gas power unit and the thermal power unit during operation, and simultaneously and differentially represents the power track and the operation characteristics of the thermal power unit under different starting types. Meanwhile, the problem of operation standby of the power system is considered, the situation that the stored energy and the unit provide rotation standby for the system together is comprehensively considered, the situation is more consistent with the actual operation situation and the actual situation, and meanwhile, the practicability is higher; the invention provides a multi-resource scheduling model of the power system, realizes multi-resource optimized scheduling of the power system, and effectively reduces waste of clean energy. Compared with the existing power system scheduling model or unit combination model, the method provided by the invention is more practical and more practical, improves the precision of the operation characteristic model of the thermal power unit in the power system scheduling analysis, provides an analysis tool for the power system to develop peak regulation resource optimization configuration decision, and has certain economic benefit and environmental benefit.
Drawings
FIG. 1 is a schematic diagram of a process flow framework of the method of the present invention.
Fig. 2 is a schematic diagram of the output trajectory of the gas turbine set in the start-stop stage.
Fig. 3 is a schematic diagram of the power output trajectory of the thermal power generating unit in the start-stop stage.
Fig. 4 is a modified PJM5 node system of the present invention.
FIG. 5 shows predicted values of wind power of each scene according to the present invention.
FIG. 6 illustrates system backup requirements for various scenarios of the present invention.
FIG. 7 is a predicted value of the load of the power system according to the present invention.
Detailed Description
The technical scheme of the invention is specifically explained below with reference to the accompanying drawings.
The invention provides an energy storage optimal configuration method considering the climbing capacity and multi-stage state transfer of a system gas and thermal power generating unit. The proposed method comprises several key steps, S1: firstly, according to historical data, the output of a new energy generator set is predicted, a typical scene set of the output of the new energy generator set (such as wind power generation) is constructed, and a load scene set of a power system is constructed by combining the load fluctuation characteristic; s2: analyzing the operating characteristics of the start-stop stages of the gas generating unit and the thermal power generating unit, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the start-stop stage operation of the gas generating unit and the thermal power generating unit, and realizing the transfer and switching between different states in the start-stop stage operation process of the gas generating unit and the thermal power generating unit; s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target; s4: and solving the energy storage optimal configuration problem of the power system to obtain an energy storage optimal configuration scheme of the power system. The method is concretely realized as follows:
s1: constructing power system operation scene set
According to the wind power output and load related statistical data, fitting a distribution function, randomly simulating by adopting a Monte-Carlo simulation method to generate a corresponding wind power output sample and a power load time sequence sample of each node, and combining the two samples to generate a power system operation scene set. And if necessary, the scene reduction technology can be used for reducing the number of scenes, keeping typical scenes, reducing the operation complexity without lacking precision and improving the operation speed of solving the problem.
The uncertainty of the wind power output and the load mainly considers the deviation of wind speed and load prediction, and the deviation of the wind power output and the load is considered to be normal load distribution. The actual values of wind speed and load can be represented after the predicted expected value and the predicted error. The form is as follows:
in the formula: v (t), PL(t) true values for wind speed and load, respectively;respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) wind speed and load prediction errors, respectively, both obeying probability distribution;
the wind power output can be calculated according to the following formula:
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed；vinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
and combining the wind power output and the load generated by the simulation to generate a power system operation scene set.
S2: multi-stage state transition modeling for gas generating unit and thermal power generating unit
The step S2 can be specifically divided into the following sub-steps: 1) analyzing the operating characteristics of the thermal power generating unit in a starting and stopping stage; 2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring 0-1 variable representing the state; 3) determining a state establishing and transferring condition of the thermal power generating unit, and establishing a state transferring equation set; 4) and writing an operating characteristic constraint equation of the thermal power unit in a row, and perfecting a start-stop stage model of the thermal power unit.
1) Thermal power generating unit start-stop stage operation characteristic analysis
In actual power system scheduling, the starting and stopping actions of the thermal power generating unit are not finished instantaneously, the thermal power generating unit meets a specific starting and stopping curve when being started and stopped, and the thermal power generating unit can still provide electric energy in the period. The start-stop process of a common thermal power generating unit needs to go through the load increasing and load reducing processes, as shown in fig. 2 and 3.
2) Thermal power generating unit state modeling
According to the operating state characteristics of the unit in the start-stop stage shown in fig. 2 and 3, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;indicating machineWhether group i is in an elevated load state at time t;indicating whether the unit n is in a scheduling receiving state at the moment t;indicating whether the unit n is in a load reduction state at the moment t;
3) set state transfer equation
According to the operating state characteristics of the unit in the start-stop stage shown in fig. 2 and 3, the following state transfer equations are introduced to represent the switching of the unit between the operating states.
yi(t)-zi(t)＝ui(t) (5)
yi(t)+zi(t)≤1 (9)
The formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; the variables in the above formulae are all variables from 0 to 1, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;the variable is a variable for controlling the unit to enter and jump out of a schedulable state;the variable is used for controlling the unit to enter and jump out of the load reduction state;
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t; the formula (17) to the formula (18) show that the output of the thermal power generating unit just entering the schedulable state and the load reduction state must be equal toP iThe connection among the states of the thermal power generating unit is ensured, and meanwhile, the two formulas are only suitable for the thermal power generating unit and are not suitable for a quick start-stop unit comprising a gas unit;
Δpi(t)＝pi(t)-pi(t-1) (19)
the output variation delta p of the unit under the normal operation state of the systems of the formula (19) and the formula (21) respectivelyi(t) the amount of change in output when the upper spinning reserve is calledAnd the amount of change in output when the lower spinning reserve is calledWherein,andis the value of upper rotation standby and lower rotation standby provided by the unit;
4) and (3) restraining the climbing rate of the unit:
wherein, Rui(t) and Rdi(t) the climbing and descending capacities of the unit at the time t and can be calculated by the following formula;
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
wherein,andis the duration of the load up and load down;
equation (26) to equation (28) are respectively the maximum and minimum output of the time group when the upper spinning standby is called and the lower spinning standby is called in the normal running state of the system; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
wherein,andrespectively starting and stopping time;andrespectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) can be calculated from formula (31);
s3: establishing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit
The objective function of the model created by the present invention is to minimize the associated investment and total operating costs.
In summary, the objective function of the model proposed by the present invention is shown in the following formula (32). The expenses in the formula are as follows: the method comprises the following steps of generating cost of the thermal power generating unit, starting cost of the thermal power generating unit, shutdown cost of the thermal power generating unit, wind abandoning penalty cost of power system scheduling, scheduling cost of DR resources and charging and discharging cost of the electric energy storage equipment.
In the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is an electric energy storage equipment set, and S belongs to S; e, wind power output scene set; generating cost, starting cost, stopping cost and standby service cost of the gas and thermal power generating unit i at the moment t are respectively set;investment costs for electrical energy storage devices;investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoss of load cost scheduled for power systemAnd unit wind abandon penalty cost; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t can be calculated by the following formulas (33) -35; the investment reserve of the electric energy storage equipment and the transmission line can be calculated according to an equation (36) and an equation (37);
in the above formulas:respectively the no-load cost and the linear power generation cost of the unit i;respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs of line lCapacity expansion is required;
the invention provides an energy storage optimization configuration method considering the climbing capacity and multi-stage state transition of a system gas and thermal power generating unit, wherein the constraint conditions of an optimization model used by the method are expressed as follows:
1) power system operating characteristic constraints
Such types of constraints include, for example, power balance, dc power flow constraints, transmission line capacity constraints, and power system backup demand constraints. Wherein the power balance constraint may be expressed in the form:
in the formula: n is a power system network topology node set;the node n is a set of the units;the wind generating set is a set of wind generating sets at the node n;is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;the scheduling value of the wind power plant j at the time t;respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
for power grid power flow constraint, a direct current power flow equation with neglected network loss is adopted, and a common expression of a direct current power flow model is as follows:
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the voltage phase angle difference of the system node n and the node k at the time t; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
the transmission line capacity constraint may be expressed in the form:
in the formula:maximum transmission capacity of a line connecting a system node n and a node k;
power system backup demand constraints:
the expressions of equations (41) and (42) apply to different types of backup requirements of the power system (e.g., 1 hour spinning backup, 15 minute spinning backup, non-spinning backup, etc.). The present invention contemplates only the 15 minute spinning standby version.
In the formula: pr (-) is a probability function;andrespectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;andα and β are confidence levels respectively meeting the upper backup and the lower backup of the system;
2) electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48).
The expressions (43) to (48) are electrical energy storage meansEnergy constraint of the equipment; es(t) is the electric energy (SOC) stored by the electric energy storage device s at the time t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;the charge-discharge efficiency of the electrical energy storage device s, respectively; γ srespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;the maximum charging and discharging power of the electrical energy storage device s is respectively; the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; equation (48) is the charge-discharge balance constraint of the electrical energy storage device under consideration of self-discharge;
3) the energy storage backup service capacity needs to satisfy the following constraints:
in the formula:andrespectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
4) unit characteristic constraints
Wind generating set output restraint
Relevant constraints such as output constraint, climbing rate constraint, minimum start-stop time constraint and the like of the gas generating unit and the thermal power generating unit are shown in the relevant expressions.
S4: solving multi-resource optimization scheduling problem of power system
The energy storage optimization configuration method which is established in the method and takes the climbing capacity and the multi-stage state transition of the gas and thermal power generating units into consideration can be linearly processed into a standard Mixed Integer Linear Programming (MILP) model, so that CPLEX can be called by a business software GAMS to be conveniently solved, and a power system scheduling decision scheme is obtained.
The energy storage optimization configuration model considering the climbing capacity and the multi-stage state transition of the gas and thermal power generating unit is further explained by combining with an example as follows:
example simulation analysis was performed using a modified PJM5 node system as an example, as shown in fig. 4. The system has 5 generators (a gas power unit and a thermal power unit), and relevant parameters of the generators are shown in a table 1. Table 2 is the operating parameters of the electrical energy storage device and table 3 is the transmission line capacity. VOLL and λwThe confidence levels α and β take values of 0.95, each time interval is 1 hour in consideration of 24 hours a day, 1 wind farm is accessed at a node 1 of the system, the installed capacity is 600MW, the output and standby requirements under each scene (S1-S5) of the wind farm are respectively shown in FIG. 5 and FIG. 6, the probability of each scene is respectively 23.22%, 18.78%, 16.08%, 21.36% and 20.56%, the total load of the system is shown in FIG. 7, and the proportion of the load of the system at nodes 2, 3, 4 and 3 to the total load is respectively 41.5%, 30.3% and 28.2%.
TABLE 1 thermal power generating unit parameters
TABLE 2 electric energy storage device scheduling parameters
Table 3 shows system indexes in different scenarios. The analysis result shows that the method provided by the invention is superior to other schemes on most system indexes because the capability of the electric energy storage equipment for providing system standby is considered. When the electric energy storage equipment is not considered to provide the standby capacity for the system, the conventional capacity can provide the standby capacity, so that the adjustment space of the unit in operation is compressed, and certain flexibility is sacrificed.
Meanwhile, the optimized configuration result also shows that the energy storage equipment configured in the power system can reduce the capacity expansion requirement of the line, and can absorb more clean energy, especially can provide a standby for the power system, provide a larger operation space for the traditional unit and enable the unit to operate in a better operation state.
TABLE 3 System indices under different scenarios
Note: "-" indicates that the indicator is not applicable in this scenario
The invention provides an energy storage optimal configuration method considering the climbing capacity and multi-stage state transition of a system gas and a thermal power unit, which represents the mutual switching and transferring relation between various states of the gas power unit and the thermal power unit during operation in a unified mode. Meanwhile, the problem of the operation and standby of the power system is considered, a power system multi-resource scheduling model is provided,
the comprehensive consideration energy storage and the unit provide the condition of rotating reserve for the system together and better accord with the actual operation condition, the actual condition is better accorded with, and the practicality is stronger simultaneously.
A multi-resource scheduling model of the power system is provided, multi-resource optimized scheduling of the power system is achieved, and waste of clean energy is effectively reduced. Compared with the existing power system scheduling model or unit combination model, the method provided by the invention is more practical and more practical, improves the precision of the operation characteristic model of the thermal power unit in the power system scheduling analysis, provides an analysis tool for the power system to develop peak regulation resource optimization configuration decision, and has certain economic benefit and environmental benefit.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.
Claims (5)
1. An energy storage optimal configuration method considering characteristics of system gas and thermal power generating units is characterized by comprising the following steps,
s1, firstly, predicting the output of the new energy generator set according to historical data, constructing a typical scene set of the output of the new energy generator set, and constructing a load scene set of the power system by combining with the load fluctuation characteristic;
s2, analyzing the operation characteristics of the gas generating unit and the thermal power generating unit in the start-stop stage, establishing a state transfer equation set, determining state transfer conditions, establishing a state transfer model for the operation of the gas generating unit and the thermal power generating unit in the start-stop stage, and realizing the transfer and switching between different states in the operation process of the gas generating unit and the thermal power generating unit in the start-stop stage;
s3: according to the system and the operation parameters, on the basis of considering a wind power consumption target, constructing an energy storage optimization configuration model considering the climbing capacity and multi-stage state transfer of a gas turbine unit and a thermal power unit by taking the minimum related investment and total operation cost as a target;
s4: and solving the energy storage optimal configuration problem of the power system to obtain an energy storage optimal configuration scheme of the power system.
2. The energy storage optimal configuration method considering characteristics of system gas and thermal power generating units according to claim 1, wherein the step S1 is implemented as follows:
uncertainty of wind power output and load mainly considers deviation of wind speed and load prediction, and respective deviation is considered to be normal load distribution; the actual values of the wind speed and the load can be represented after the predicted expected value and the predicted error; the form is as follows:
in the formula: v (t), PL(t) true values for wind speed and load, respectively;respectively predicting expected values for wind speed and load; e.g. of the typev(t)、eL(t) wind speed and load prediction errors, respectively, both obeying probability distribution;
the wind power output can be calculated according to the following formula:
in the formula: p (v) is the output of the wind turbine generator at the wind speed v; v is the wind speed; v. ofinCutting wind speed for the wind driven generator; v. ofrThe rated power wind speed of the wind driven generator; v. ofoutCutting wind speed for the wind driven generator; (v) wind speed vinTo vrIn time, the function of the relation between the output power of the wind driven generator and the wind speed; pmaxThe rated power of the wind turbine generator is set;
and combining the wind power output and the load generated by the simulation to generate a power system operation scene set.
3. The energy storage optimal configuration method considering characteristics of system gas and thermal power generating units according to claim 2, wherein the step S2 is implemented as follows:
1) analyzing the operating characteristics of the thermal power generating unit in the starting and stopping stage: the starting and stopping processes of the thermal power generating unit need to go through the load increasing and load reducing processes;
2) modeling the state of the thermal power generating unit, determining the number of running states, and configuring a 0-1 variable representing the state: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, 4 variables 0-1 are introduced to represent the operating state of the unit: u. ofi(t)、Wherein: u. ofi(t) indicates whether the unit i is in an operating and shutdown state at the moment t;indicating whether the unit i is in a load-up state at the moment t;indicating whether the unit n is in a scheduling receiving state at the moment t;indicating whether the unit n is in a load reduction state at the moment t;
3) defining the state establishing and transferring condition of the thermal power generating unit, and establishing a state transferring equation set: according to the operating state characteristics of the thermal power generating unit in the starting and stopping stage, the following state transfer equation set is introduced to represent the switching of the thermal power generating unit among the operating states;
yi(t)-zi(t)＝ui(t) (5)
yi(t)+zi(t)≤1 (9)
the formula (4) ensures that the unit can only be in a unique state each time; the formula (5) to the formula (12) represent a state transition model and logic constraints of the unit operation state; equation (13) -equation (16) represent a constraint relationship from one state to another state at the time of state transition; the variables in the above formulae are all variables from 0 to 1, wherein: y isi(t)、zi(t) is a variable for controlling the starting and stopping states of the unit;the variable is a variable for controlling the unit to enter and jump out of the load-lifting state;the variable is a variable for controlling the unit to enter and jump out of a schedulable state;the variable is used for controlling the unit to enter and jump out of the load reduction state;
wherein M represents a large positive number, pi(t) is the output of the unit i at the moment t; the formula (17) -formula (18) shows that the power output of the thermal power generating unit just after entering the schedulable state and the load reduction state must be PiThe connection between the states of the thermal power generating unit is ensured, and the two states are noteworthyThe formula is only suitable for thermal power generating units and is not suitable for quick start-stop units including gas units;
Δpi(t)＝pi(t)-pi(t-1) (19)
the output variation delta p of the unit under the normal operation state of the systems of the formula (19) and the formula (21) respectivelyi(t) the amount of change in output when the upper spinning reserve is calledAnd the amount of change in output when the lower spinning reserve is calledWherein,andis the value of upper rotation standby and lower rotation standby provided by the unit;
4) writing a thermal power unit operation characteristic constraint equation in a column mode, and perfecting a thermal power unit start-stop stage model:
wherein, Rui(t) and Rdi(t) the climbing and descending capacities of the unit at the time t and can be calculated by the following formula;
wherein, IthermalIs a thermal power generating unit set; i isgasIs a gas turbine set; RU (RU)iAnd RDiThe up-climbing and down-climbing capacities of the unit under the adjustable state are achieved;the climbing capacity and the climbing capacity of the unit in the load ascending state and the load descending state are calculated according to the following formula;
wherein,andis the duration of the load up and load down;
equation (26) to equation (28) are respectively the maximum and minimum output of the time group when the upper spinning standby is called and the lower spinning standby is called in the normal running state of the system; equation (29) is the constraint of the maximum minimum up-down rotation reserve capacity of the unit;
the minimum start-stop time constraint of the unit is shown as follows:
wherein, Ti on(T) and Ti off(t) start-up and shut-down times, respectively;andrespectively minimum startup and minimum shutdown time;
under the condition of the output curve of the piecewise linearization unit, the generated electricity quantity e of the uniti(t) can be calculated from formula (31);
4. the energy storage optimal configuration method considering characteristics of system gas and thermal power generating units according to claim 3, wherein the step S3 is implemented as follows:
1) an energy storage optimization configuration model objective function considering the climbing capacity and the multi-stage state transition of the gas power unit and the thermal power unit is constructed as follows:
in the formula: n is a power system network topology node set; t is a scheduling time interval set; i is a gas and thermal power generating unit set, I belongs to I; j is a wind generating set; s is electricity storageEnergy equipment is collected, and S belongs to S; e, wind power output scene set; generating cost, starting cost, stopping cost and standby service cost of the gas and thermal power generating unit i at the moment t are respectively set;investment costs for electrical energy storage devices;investment cost for the transmission line; pr (total reflection)εThe probability of occurrence of the wind power output scene epsilon is determined; VOLL and λwLoad loss cost and unit wind abandon punishment cost for power system scheduling; the last two parts of the above equation are expectations for conditional risk values for upper and lower spares;
the power generation cost, the starting cost, the shutdown cost and the standby service cost of the gas and thermal power generating unit i at the moment t can be calculated by the following formulas (33) -35; the investment reserve of the electric energy storage equipment and the transmission line can be calculated according to an equation (36) and an equation (37);
in the above formulas:respectively the no-load cost and the linear power generation cost of the unit i;respectively starting, stopping, up-standby and down-standby service fees of the unit at a single time or unit capacity; c. CmAnd cpThe investment cost required for allocating unit capacity and unit power electric energy storage equipment respectively; l is a set of transmission lines; c. ClineInvestment costs required to build a unit capacity line; plIs the capacity expansion requirement of line l;
2) the method comprises the following steps of constructing energy storage optimization configuration model constraint conditions considering the climbing capacity and multi-stage state transition of a gas power unit and a thermal power unit as follows:
2.1) Power System operating characteristic constraints
The power system operation characteristic constraints comprise power balance, direct current power flow constraint, transmission line capacity constraint and power system standby requirement constraint;
① the power balance constraint may be expressed in the form:
in the formula: n is a power system network topology node set;the node n is a set of the units;the wind generating set is a set of wind generating sets at the node n;is a set of electrical energy storage devices at node n; p is a radical ofi(t) is the output of the unit i at the moment t;the scheduling value of the wind power plant j at the time t;respectively charging and discharging power of the electric energy storage device s at the moment t; dn(t) is the load demand of the load node n at the time t;
②, direct current power flow constraint, adopting a direct current power flow equation neglecting network loss, and the common expression of the direct current power flow model is as follows:
in the formula: b isn,kAn imaginary part of an admittance matrix of the grid node; delta thetaε,n,k(t) is the voltage phase angle difference of the system node n and the node k at the time t; thetaε,n(t)、θε,k(t) the voltage phase angles of the system node n and the node k at the moment t respectively; x is the number ofn,kIs the line impedance of node n and node k;
③ the transmission line capacity constraint may be expressed in the form:
in the formula:maximum transmission capacity of a line connecting a system node n and a node k;
④ Power System backup requirement constraints the expressions of equations (41) and (42) apply to different types of backup requirements of the power system:
in the formula: pr (-) is a probability function;andrespectively providing upper standby values and lower standby values for the system according to the electric energy storage obtained by the wind power prediction and the load prediction errors;andα and β are confidence levels respectively meeting the upper backup and the lower backup of the system;
2.2) Electrical energy storage device operating characteristic constraints
The electrical energy storage device operating characteristic constraints are as shown in equations (43) - (48):
equations (43) - (48) are energy constraints of the electrical energy storage device; es(t) is the electric energy stored by the electric energy storage device s at the moment t; deltasThe loss coefficient under self-discharge condition of the electrical energy storage device s;the charge-discharge efficiency of the electrical energy storage device s, respectively;γsrespectively representing the SOC upper limit coefficient and the SOC lower limit coefficient of the electric energy storage equipment s;is the rated capacity of the electrical energy storage device s; equations (45) - (46) are the charge and discharge power constraints of the electrical energy storage device;the maximum charging and discharging power of the electrical energy storage device s is respectively; the charging and discharging working states of the electric energy storage equipment s are respectively 0-1 variable; equation (47) is the electrical energy storage device operating state constraint; equation (48) is the charge-discharge balance constraint of the electrical energy storage device under consideration of self-discharge;
2.3) energy storage Standby service Capacity
The energy storage backup service capacity needs to satisfy the following constraints:
in the formula:andrespectively calling SOC values of upper standby time electric energy storage equipment and lower standby time electric energy storage equipment for the system;
2.4) wind generating set output restraint
The output of the wind generating set is restricted as follows:
in the formula:and the output value of the wind farm j at the moment t is shown.
5. The energy storage optimization configuration method considering the characteristics of the system gas and the thermal power generating unit as claimed in claim 1 or 4, wherein in the step S4, the established energy storage optimization configuration method considering the climbing capability and the multi-stage state transition of the gas and thermal power generating unit is linearized into a standard mixed integer linear programming model, and then CPLEX is called by using business software GAMS to facilitate solving, so as to obtain a power system scheduling decision scheme.
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| CN112564186B (en) * | 2020-12-11 | 2022-06-14 | 中国电力科学研究院有限公司 | Energy storage power and capacity planning method and system for assisting thermal power generating unit in deep peak shaving |
| CN112564186A (en) * | 2020-12-11 | 2021-03-26 | 中国电力科学研究院有限公司 | Energy storage power and capacity planning method and system for assisting thermal power generating unit in deep peak shaving |
| CN112797437A (en) * | 2021-02-03 | 2021-05-14 | 华能武汉发电有限责任公司 | Intelligent air supply control method, equipment and storage medium |
| CN112797437B (en) * | 2021-02-03 | 2022-03-22 | 华能武汉发电有限责任公司 | Intelligent air supply control method, equipment and storage medium |
| CN114285088B (en) * | 2021-11-29 | 2023-10-10 | 中国华能集团清洁能源技术研究院有限公司 | Energy system optimal configuration method and system considering thermal power unit constraint |
| CN114285088A (en) * | 2021-11-29 | 2022-04-05 | 中国华能集团清洁能源技术研究院有限公司 | Energy system optimal configuration method and system considering thermal power generating unit constraints |
| CN114498637B (en) * | 2022-04-13 | 2022-07-12 | 清华四川能源互联网研究院 | Method for analyzing influence of new energy field configuration energy storage on utilization rate |
| CN114498637A (en) * | 2022-04-13 | 2022-05-13 | 清华四川能源互联网研究院 | Method for analyzing influence of new energy field configuration energy storage on utilization rate |
| CN114552672A (en) * | 2022-04-26 | 2022-05-27 | 阿里巴巴（中国）有限公司 | Data processing method and storage medium for power system |
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