CN109149571B - Energy storage optimal configuration method considering characteristics of system gas and thermal power generating unit - Google Patents

Abstract

The invention relates to an energy storage optimal configuration method considering system gas and thermal power generating units. The method comprises the following steps: 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 is constructed, and a load scene set of a power system is constructed in combination with load fluctuation characteristics; 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; 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; and solving the energy storage optimization configuration problem of the power system to obtain an energy storage optimization configuration scheme of the power system.

Description

An optimal allocation method for energy storage considering the characteristics of system gas and thermal power units

technical field

The invention belongs to the technical field of power system planning, and particularly relates to an energy storage optimization configuration method considering the characteristics of system gas and thermal power units.

Background technique

The environmental problems brought about by the extensive economic development model make renewable energy (such as wind energy) attract attention because of its green environmental friendliness. Large-scale clean energy access is bound to improve the environment, but it also brings new challenges to the operation of the power system. Insufficient peak capacity has become the main factor restricting clean energy consumption capacity. On the one hand, the power grid needs to have a more flexible operation mode to improve the adjustment capability of the power system; on the other hand, in the process of power system planning (especially flexible resources including energy storage), it is necessary to fully consider the renewable energy Volatility and intermittency give the grid the ability to actively access clean energy.

In order to cope with the uncertainty brought about by the access of new energy sources, the power system requires more backup resources than the traditional operation mode. At present, when the power system solves the backup optimization problem, it has not considered whether each resource in the system has the ability to accept the command for system backup scheduling during the operation process. In order to solve the above problems, it is necessary to fully consider the operating characteristics of each resource of the system (for example, the unit needs to consider the starting and stopping characteristics and ramping characteristics, and the energy storage needs to consider the limitation of the SOC range, etc.), and then propose a more refined operation model.

Based on this, the present invention comprehensively considers the operating characteristics and ramping capability of gas and thermal power units during start-stop phases, and proposes an energy storage optimization configuration method that considers the ramping capability and multi-stage state transition of the system gas and thermal power units.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide an energy storage optimization configuration method considering the characteristics of the system gas and thermal power units, which can characterize the mutual switching and transfer relationship between the states of the gas turbine and the thermal power unit during operation, and at the same time differentiate the thermal power units. Power trajectories and operating characteristics for different start-up types. At the same time, considering the operation backup of the power system, comprehensively considering the situation that the energy storage and the unit jointly provide the rotating backup for the system is more in line with the actual operation situation, more in line with the actual situation, and more practical.

In order to achieve the above object, the technical scheme of the present invention is: a method for optimizing the configuration of energy storage considering the characteristics of system gas and thermal power units, comprising the following steps:

S1. First, according to the historical data, predict the output of the new energy generator set, construct a typical scenario set of the output of the new energy generator set, and combine the load fluctuation characteristics to construct a load scenario set of the power system;

S2. Analyze the operating characteristics of gas and thermal power units during the start-stop phase, establish state transition equations, clarify the state transition conditions, and establish a state transition model for gas and thermal power units in the start and stop phases of operation, so as to realize the start-up and shutdown of gas and thermal power units. Transfer and switch between different states during the stop phase operation;

S3: According to the system and operating parameters, on the basis of considering the wind power consumption target, with the goal of minimizing the relevant investment and total operating cost, construct an energy storage optimal configuration model that considers the climbing ability and multi-stage state transition of gas-fired and thermal power units ;

S4: Solve the above power system energy storage optimization configuration problem, and obtain the power system energy storage optimization configuration scheme.

In an embodiment of the present invention, the step S1 is specifically implemented as follows:

The uncertainty of wind power output and load mainly considers the deviation of wind speed and load prediction, and it is considered that the respective deviations are the normal distribution of load; the true values of wind speed and load can be expressed by the predicted expected value and the predicted error; the form is as follows:

分别为风速和负荷预测期望值；e_v(t)、e_L(t)分别为风速和负荷预测误差，二者均服从概率分布；where v(t) and _PL (t) are the actual values of wind speed and load, respectively;

are the wind speed and load forecast expected values, respectively; e _v (t) and e _L (t) are the wind speed and load forecast errors, respectively, both of which obey the 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 at the wind speed v; v is the wind speed; v _in is the cut-in wind speed of the wind turbine; v _r is the rated power wind speed of the wind turbine; v _out is the cut-in wind speed of the wind turbine. wind speed; f(v) is the function of the relationship between the output power of the wind turbine and the wind speed when the wind speed is between v _in and v _r ; P _max is the rated power of the wind turbine;

The wind power output and load generated by the above simulation are combined to generate a set of power system operation scenarios.

In an embodiment of the present invention, the step S2 is specifically implemented as follows:

1) Analyze the operating characteristics of the thermal power unit during the start-stop phase: the start-stop process of the thermal power unit needs to go through the process of increasing and decreasing the load;

其中：u_i(t)表示机组i在时刻t是否处于运行和停机状态；

表示机组i在时刻t是否处于升负荷状态；

表示机组n在时刻t是否处于接受调度的状态；

表示机组n在时刻t是否处于降负荷状态；2) Model the state of the thermal power unit, determine the number of operating states, and configure the 0-1 variables that characterize the state: According to the operating state characteristics of the thermal power unit during the start and stop phases, four 0-1 variables are introduced to represent the operating state of the unit: u _i (t) ,

Among them: u _i (t) indicates whether the unit i is in the running and shutdown state at time t;

Indicates whether unit i is in a load-up state at time t;

Indicates whether unit n is in the state of accepting scheduling at time t;

Indicates whether unit n is in a reduced load state at time t;

3) Clarify the state transition conditions of the thermal power unit, and establish a state transition equation system: According to the operating state characteristics of the thermal power unit during the start and stop phases, the following state transition equations are introduced to represent the switch between the operating states of the unit;

y _i (t)-z _i (t)=u _i (t) (5)

y _i (t)+z _i (t)≤1 (9)

为控制机组进入、跳出升负荷状态的变量；

为控制机组进入、跳出可调度状态的变量；

为控制机组进入、跳出降负荷状态的变量；Equation (4) ensures that the unit can only be in a unique state each time; Equation (5)-Equation (12) are the state transition model and logic constraints representing the operating state of the unit; Equation (13)-Equation (16) represent the state transition The constraint relationship from one state to another state; the variables in the above formulas are all 0-1 variables, among which: y _i (t), z _i (t) are variables that control the start and stop states of the unit;

It is a variable that controls the unit to enter and exit the state of increasing the load;

Variables that control the unit to enter and exit the schedulable state;

It is a variable to control the unit entering and exiting the load reduction state;

Among them, M represents a large positive number, p _i (t) is the output of unit i at time t; Equation (17)-Equation (18) indicate that the output of the thermal power unit when it just enters the dispatchable state and the load reduction state must be is P _i , which ensures the connection between the states of thermal power units, and it is worth noting that the above two formulas are only applicable to thermal power units, not suitable for quick start-stop units including gas-fired units;

_Δpi (t)= _pi (t) _-pi (t-1) (19)

和下旋转备用被调用时的出力变化量

其中，

和

是机组所提供上旋转备用和下旋转备用的值；Equation (19)-Equation (21) are respectively the output change Δp _i (t) of the unit under the normal operating state of the system, and the output change when the upper spinning reserve is called

and the amount of output change when the lower spinning reserve is called

in,

and

is the value of upper spinning reserve and lower spinning reserve provided by the unit;

4) Write down the constraint equation of thermal power unit operating characteristics, and improve the start-stop stage model of thermal power unit:

Among them, Ru _i (t) and Rd _i (t) are the climbing and descending capabilities of the unit at time t, and can be calculated by the following formula;

分别是机组在升负荷和降负荷状态下的上爬坡和下爬坡能力，二者可通过下式计算；Among them, I _thermal is the set of thermal power units; I _gas is the set of gas-fired units; RU _i and RD _i are the up-climbing and down-climbing capabilities of the unit in the dispatchable state;

are the climbing and descending capacities of the unit under load-up and load-down states, respectively, which can be calculated by the following formulas;

和

是升负荷和降负荷的持续时间；in,

and

is the duration of load raising and lowering;

Equations (26)-(28) are respectively the maximum and minimum output of the unit when the upper spinning reserve is called and the lower spinning reserve is called in the normal operation state of the system; Equation (29) is the constraint of the maximum and minimum upper and lower spinning reserve capacity of the unit;

The minimum start and stop time constraints of the unit are as follows:

和

分别是启机和停机时间；

和

分别为最小启机和最小停机时间；in,

and

are the startup and shutdown times, respectively;

and

are the minimum startup and minimum downtime, respectively;

In the case of piecewise linearization of the output curve of the unit, the power generation e _i (t) of the unit can be calculated by formula (31);

In an embodiment of the present invention, the step S3 is specifically implemented as follows:

1) The objective function of the energy storage optimization configuration model considering the ramping ability and multi-stage state transition of gas and thermal power units is constructed as follows:

分别为燃气和火电机组i在t时刻的发电费用、启动费用、停机费用和备用服务费用；

为电储能设备的投资费用；

为输电线路的投资费用；pr_ε为风电出力场景ε发生概率；VOLL和λ^w为电力系统调度的失负荷成本和单位弃风惩罚成本；上式最后两部分是上备用和下备用的条件风险值的期望；In the formula: N is the set of power system network topology nodes; T is the set of scheduling time periods; I is the set of gas and thermal power units, i∈I; J is the set of wind turbines; S is the set of electric energy storage equipment, s∈S; E Wind output scene collection;

are the power generation cost, start-up cost, shutdown cost and backup service cost of gas and thermal power unit i at time t, respectively;

The investment cost of electric energy storage equipment;

is the investment cost of the transmission line; pr _ε is the probability of occurrence of the wind power output scenario ε; VOLL and λ ^w are the loss of load cost and the unit wind curtailment penalty cost of power system dispatching; the last two parts of the above formula are the conditional risks of upper and lower backup value expectations;

The power generation cost, start-up cost, shutdown cost and backup service cost of gas-fired and thermal power unit i at time t can be calculated by the following formulas (33)-(35); the investment and backup of electric energy storage equipment and transmission lines can be calculated according to formula ( 36) and formula (37) calculation;

分别为机组i的空载费用、线性发电费用；

分别为单次或单位容量下的机组启动、停止、上备用、下备用服务费用；c_m和c_p分别为配备单位容量和单位功率电储能设备所需要的投资费用；L为输电线路的集合；c_line为建设单位容量线路所需要的投资费用；P_l是线路l的扩容需求；In the above formulas:

are the no-load cost and linear power generation cost of unit i, respectively;

are the starting, stopping, upper-backup, lower-backup service costs of a single unit or unit capacity, respectively; _cm and _cp are the investment costs required to equip unit capacity and unit power electric energy storage equipment, respectively; L is the transmission line set; c _line is the investment cost required to build a unit capacity line; P _l is the capacity expansion demand of line l;

2) Construct the optimal configuration model of energy storage considering the ramping ability and multi-stage state transition of gas and thermal power units. The constraints are as follows:

2.1) Constraints of power system operating characteristics

Power system operating characteristic constraints, including power balance, DC power flow constraints, transmission line capacity constraints, and power system reserve demand constraints;

① The power balance constraint can be expressed in the following form:

为节点n处机组的集合；

为节点n处风力发电机组的集合；

为节点n处电储能设备的集合；p_i(t)为机组i在t时刻的出力；

为风电场j在t时刻的调度值；

分别为电储能设备s在t时刻的充、放电功率；D_n(t)为负荷节点n在t时刻的负荷需求；In the formula: N is the set of power system network topology nodes;

is the set of units at node n;

is the set of wind turbines at node n;

is the set of electric energy storage devices at node n; p _i (t) is the output of unit i at time t;

is the dispatch value of wind farm j at time t;

are the charging and discharging power of the electric energy storage device s at time t, respectively; D _n (t) is the load demand of load node n at time t;

② DC power flow constraints, adopt the DC power flow equation that ignores the network loss, and the common expressions of the DC power flow model are as follows:

Where: B _n,k is the imaginary part of the grid node admittance matrix; Δθ _ε,n,k (t) is the voltage phase angle difference between node n and node k of the system at time t; θ _ε,n (t), θ _{ε, k} (t) are the voltage phase angles of node n and node k of the system at time t, respectively; x _{n, k} are the line impedances of node n and node k;

③ The capacity constraints of transmission lines can be expressed in the following form:

为连接系统节点n和节点k线路的最大传输容量；where:

is the maximum transmission capacity of the line connecting the system node n and node k;

④ Reserve demand constraints of the power system: The expressions of equations (41) and (42) are applicable to different types of reserve demands of the power system:

和

分别为根据风电预测和负荷预测误差所得到电储能为系统提供上备用和下备用的值；

和

分别为电力系统上备用下备用的需求，可通过风电和负荷预测误差估计；α和β分别为满足系统上备用和下备用的置信度水平；In the formula: Pr( ) is the probability function;

and

are the values of the upper and lower backups provided by the electric energy storage for the system according to the wind power forecast and the load forecast error, respectively;

and

are the upper and lower backup requirements of the power system, which can be estimated by wind power and load forecast errors; α and β are the confidence levels for meeting the upper and lower backup of the system, respectively;

2.2) Operating characteristic constraints of electric energy storage equipment

The operating characteristic constraints of electric energy storage equipment are shown in equations (43)-(48):

分别为电储能设备s的充放电效率；

γ _s分别为电储能设备s的SOC上、下限系数；

为电储能设备s的额定容量；式(45)-(46)是电储能设备的充、放电功率约束；

分别为电储能设备s的最大充、放电功率；

分别为电储能设备s的充、放电工作状态，是0-1变量；式(47)是电储能设备工作状态约束；式(48)是电储能设备在考虑自放电情况下的充放电平衡约束；Equations (43)-(48) are the energy constraints of the electric energy storage device; E _s (t) is the electric energy stored by the electric energy storage device s at time t; δ _s is the self-discharge condition of the electric energy storage device s loss factor;

are the charge and discharge efficiencies of the electric energy storage device s, respectively;

γs are the upper and lower limit coefficients of the SOC of the electric energy storage device _s , respectively;

is the rated capacity of the electric energy storage device s; formulas (45)-(46) are the charge and discharge power constraints of the electric energy storage device;

are the maximum charging and discharging power of the electric energy storage device s, respectively;

are the charging and discharging working states of the electric energy storage device s, respectively, which are 0-1 variables; Equation (47) is the working state constraint of the electric energy storage device; Equation (48) is the charging and discharging state of the electric energy storage device considering self-discharge. Discharge balance constraints;

2.3) Reserve service capacity of energy storage

The energy storage backup service capacity must meet the following constraints:

和

分别为系统调用上备用和下备用时电储能设备的SOC值；where:

and

are the SOC values of the electric energy storage device when the system calls the upper backup and lower backup, respectively;

2.4) Output constraints of wind turbines

The output constraints of the wind turbine are as follows:

为风电场j在t时刻的出力值；where:

is the output value of wind farm j at time t;

In an embodiment of the present invention, in the step S4, the established energy storage optimization configuration method considering the climbing ability and multi-stage state transition of the gas and thermal power units is linearized into a standard mixed integer linear programming model, and then adopted The commercial software GAMS invokes CPLEX to facilitate the solution and obtain the power system scheduling decision-making scheme.

Compared with the prior art, the present invention has the following beneficial effects: the method of the present invention proposes a unified form to characterize the mutual switching and transfer relationship between the states of the gas-fired unit and the thermal power unit during operation, and at the same time to differentiate the thermal power unit. Power trajectories and operating characteristics for different start-up types. At the same time, considering the operation backup problem of the power system, comprehensively considering the situation that the energy storage and the unit jointly provide rotating backup for the system is more in line with the actual operation situation, more in line with the actual situation, and more practical; the present invention proposes a multi-resource scheduling model of the power system to realize Optimal scheduling of multiple resources in the power system can effectively reduce the waste of clean energy. Compared with the existing power system scheduling model or unit combination model, the proposed method is more realistic and more practical. It improves the accuracy of the thermal power unit operating characteristic model in the power system scheduling analysis, and makes the optimal allocation decision for peak shaving resources for the power system. Provides analytical tools with certain economic and environmental benefits.

Description of drawings

FIG. 1 is a schematic diagram of the process frame of the method of the present invention.

FIG. 2 is a schematic diagram of the output trajectory of the gas generating unit in the start-stop phase of the present invention.

FIG. 3 is a schematic diagram of the output trajectory of the thermal power unit in the start and stop phases of the present invention.

Fig. 4 is the PJM5 node system modified by the present invention.

FIG. 5 is the predicted value of wind power in each scene of the present invention.

FIG. 6 shows the system backup requirements in each scenario of the present invention.

FIG. 7 is the load prediction value of the power system of the present invention.

Detailed ways

The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

The present invention proposes a method for optimizing energy storage configuration considering the ramping capability and multi-stage state transition of the system gas and thermal power units. The proposed method includes the following key steps, S1: First, based on historical data, predict the output of new energy generating units, construct a typical set of output scenarios for new energy generating units (such as wind power), and combine the load fluctuation characteristics to construct the load of the power system. Scenario set; S2: Analyze the operating characteristics of gas and thermal power units during the start-stop phase, establish state transition equations, clarify the state transition conditions, and establish a state transition model for gas and thermal power units in the start-stop phase of operation. The transition and switching between different states during the start-up and shutdown of the thermal power unit; S3: According to the system and operating parameters, on the basis of considering the wind power consumption target, the relevant investment and total operating cost are minimized as the goal, and the construction of the gas-fired unit and the The energy storage optimization configuration model of thermal power unit's climbing ability and multi-stage state transition; S4: Solve the above power system energy storage optimization configuration problem, and obtain the power system energy storage optimization configuration scheme. The specific implementation of this method is as follows:

S1: Build a power system operation scenario set

According to the relevant statistical data of wind power output and load, the distribution function is fitted, and the corresponding wind power output sample and each node power load time series sample are generated randomly by Monte-Carlo simulation method, and the two samples are combined to generate the power system operation scene set. If necessary, scene reduction technology can be used to reduce the number of scenes, retain typical scenes, reduce the computational complexity without lack of precision, and improve the computational speed of solving problems.

The uncertainty of wind power output and load mainly considers the deviation of wind speed and load prediction, and it is considered that the respective deviations are normally distributed in the load. The true values of wind speed and load can be represented by the predicted expected value and the predicted error. The form is as follows:

分别为风速和负荷预测期望值；e_v(t)、e_L(t)分别为风速和负荷预测误差，二者均服从概率分布；where v(t) and _PL (t) are the actual values of wind speed and load, respectively;

are the wind speed and load forecast expected values, respectively; e _v (t) and e _L (t) are the wind speed and load forecast errors, respectively, both of which obey the 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 at the wind speed v; v is the wind speed; v _in is the cut-in wind speed of the wind turbine; v _r is the rated power wind speed of the wind turbine; v _out is the cut-in wind speed of the wind turbine. wind speed; f(v) is the function of the relationship between the output power of the wind turbine and the wind speed when the wind speed is between v _in and v _r ; P _max is the rated power of the wind turbine;

The wind power output and load generated by the above simulation are combined to generate a set of power system operation scenarios.

S2: Multi-stage state transition modeling for gas and thermal power plants

Step S2 can be specifically divided into the following sub-steps: 1) analyzing the operating characteristics of the thermal power unit during the start-stop phase; 2) modeling the state of the thermal power unit, determining the number of operating states, and configuring the 0-1 variable representing the state; 3) clarifying the thermal power unit Establish transition conditions for the unit state, and establish state transition equations; 4) Write down the constraint equations of thermal power units operating characteristics, and improve the start-stop phase model of thermal power units.

1) Analysis of operating characteristics of thermal power units during start and stop phases

In the actual power system scheduling, the start-up and shutdown of thermal power units are not instantaneous, and the units meet a specific start-stop curve during startup and shutdown, and thermal power units can still provide electrical energy during this period. The process of starting and stopping a common thermal power unit needs to go through the process of increasing and decreasing the load, as shown in Figure 2 and Figure 3.

2) State modeling of thermal power units

其中：u_i(t)表示机组i在时刻t是否处于运行和停机状态；

表示机组i在时刻t是否处于升负荷状态；

表示机组n在时刻t是否处于接受调度的状态；

表示机组n在时刻t是否处于降负荷状态；According to the operating state characteristics of the unit in the start-stop phase shown in Figure 2 and Figure 3, four 0-1 variables are introduced to represent the operating state of the unit: u _i (t),

Among them: u _i (t) indicates whether the unit i is in the running and shutdown state at time t;

Indicates whether unit i is in a load-up state at time t;

Indicates whether unit n is in the state of accepting scheduling at time t;

Indicates whether unit n is in a reduced load state at time t;

3) Unit state transition equation

According to the operating state characteristics of the unit in the start-stop phase shown in Figure 2 and Figure 3, the following state transition equations are introduced to represent the unit's switching between various operating states.

y _i (t)-z _i (t)=u _i (t) (5)

y _i (t)+z _i (t)≤1 (9)

为控制机组进入、跳出升负荷状态的变量；

为控制机组进入、跳出可调度状态的变量；

为控制机组进入、跳出降负荷状态的变量；Equation (4) ensures that the unit can only be in a unique state each time; Equation (5)-Equation (12) are the state transition model and logic constraints representing the operating state of the unit; Equation (13)-Equation (16) represent the state transition The constraint relationship from one state to another state; the variables in the above formulas are all 0-1 variables, where: y _i (t), z _i (t) are variables that control the start-up and shutdown states of the unit;

It is a variable that controls the unit to enter and exit the state of increasing the load;

Variables that control the unit to enter and exit the schedulable state;

It is a variable to control the unit entering and exiting the load reduction state;

Among them, M represents a large positive number, p _i (t) is the output of unit i at time t; Equation (17)-Equation (18) indicate that the output of the thermal power unit when it just enters the dispatchable state and the load reduction state must be is P _i , which ensures the connection between the states of thermal power units, and it is worth noting that the above two formulas are only applicable to thermal power units, not suitable for quick start-stop units including gas-fired units;

_Δpi (t)= _pi (t) _-pi (t-1) (19)

和下旋转备用被调用时的出力变化量

其中，

和

是机组所提供上旋转备用和下旋转备用的值；Equation (19)-Equation (21) are respectively the output change Δp _i (t) of the unit under the normal operating state of the system, and the output change when the upper rotating reserve is called

and the amount of output change when the lower spinning reserve is called

in,

and

is the value of upper spinning reserve and lower spinning reserve provided by the unit;

4) Unit ramp rate constraints:

Among them, Ru _i (t) and Rd _i (t) are the climbing and descending capabilities of the unit at time t, and can be calculated by the following formula;

分别是机组在升负荷和降负荷状态下的上爬坡和下爬坡能力，二者可通过下式计算；Among them, I _thermal is the set of thermal power units; I _gas is the set of gas-fired units; RU _i and RD _i are the up-climbing and down-climbing capabilities of the unit in the dispatchable state;

are the climbing and descending capacities of the unit under load-up and load-down states, respectively, which can be calculated by the following formulas;

和

是升负荷和降负荷的持续时间；in,

and

is the duration of load raising and lowering;

Equations (26)-(28) are respectively the maximum and minimum output of the unit when the upper spinning reserve is called and the lower spinning reserve is called in the normal operation state of the system; Equation (29) is the constraint of the maximum and minimum upper and lower spinning reserve capacity of the unit;

The minimum start and stop time constraints of the unit are as follows:

和

分别是启机和停机时间；

和

分别为最小启机和最小停机时间；in,

and

are the startup and shutdown times, respectively;

and

are the minimum startup and minimum downtime, respectively;

In the case of piecewise linearization of the output curve of the unit, the power generation e _i (t) of the unit can be calculated by formula (31);

S3: Establish an energy storage optimal configuration model considering the ramping capability and multi-stage state transition of gas and thermal power units

The objective function of the model established by the present invention is to minimize the relevant investment and total operating cost.

To sum up, the objective function of the model proposed by the present invention is shown in the following formula (32). The various costs in the formula are in order: the power generation cost of the thermal power unit, the start-up cost of the thermal power unit, the shutdown cost of the thermal power unit, the penalty fee for the power system dispatching wind curtailment, the dispatching cost of the DR resource, and the charge and discharge cost of the electric energy storage equipment. cost.

分别为燃气和火电机组i在t时刻的发电费用、启动费用、停机费用和备用服务费用；

为电储能设备的投资费用；

为输电线路的投资费用；pr_ε为风电出力场景ε发生概率；VOLL和λ^w为电力系统调度的失负荷成本和单位弃风惩罚成本；上式最后两部分是上备用和下备用的条件风险值的期望；In the formula: N is the set of power system network topology nodes; T is the set of scheduling time periods; I is the set of gas and thermal power units, i∈I; J is the set of wind turbines; S is the set of electric energy storage equipment, s∈S; E Wind output scene collection;

are the power generation cost, start-up cost, shutdown cost and backup service cost of gas-fired and thermal power unit i at time t, respectively;

The investment cost of electric energy storage equipment;

is the investment cost of the transmission line; pr _ε is the probability of occurrence of the wind power output scenario ε; VOLL and λ ^w are the loss of load cost and the unit wind curtailment penalty cost of power system dispatch; the last two parts of the above formula are the conditional risks of upper and lower backup value expectations;

The power generation cost, start-up cost, shutdown cost and backup service cost of gas-fired and thermal power unit i at time t can be calculated by the following formulas (33)-(35); the investment and backup of electric energy storage equipment and transmission lines can be calculated according to formula ( 36) and formula (37) calculation;

分别为机组i的空载费用、线性发电费用；

分别为单次或单位容量下的机组启动、停止、上备用、下备用服务费用；c_m和c_p分别为配备单位容量和单位功率电储能设备所需要的投资费用；L为输电线路的集合；c_line为建设单位容量线路所需要的投资费用；P_l是线路l的扩容需求；In the above formulas:

are the no-load cost and linear power generation cost of unit i, respectively;

are the starting, stopping, upper-backup, lower-backup service costs of a single unit or unit capacity, respectively; _cm and _cp are the investment costs required to equip unit capacity and unit power electric energy storage equipment, respectively; L is the transmission line set; c _line is the investment cost required to build a unit capacity line; P _l is the capacity expansion demand of line l;

The present invention proposes an energy storage optimization configuration method that considers the ramping ability and multi-stage state transition of the gas and thermal power units of the system. The constraints of the optimization model used by the method are expressed as follows:

1) Constraints on the operating characteristics of the power system

Such constraints include, for example, power balance, DC power flow constraints, transmission line capacity constraints, and power system reserve demand constraints. The power balance constraint can be expressed in the following form:

为节点n处机组的集合；

为节点n处风力发电机组的集合；

为节点n处电储能设备的集合；p_i(t)为机组i在t时刻的出力；

为风电场j在t时刻的调度值；

分别为电储能设备s在t时刻的充、放电功率；D_n(t)为负荷节点n在t时刻的负荷需求；In the formula: N is the set of power system network topology nodes;

is the set of units at node n;

is the set of wind turbines at node n;

is the set of electrical energy storage devices at node n; p _i (t) is the output of unit i at time t;

is the dispatch value of wind farm j at time t;

are the charging and discharging power of the electric energy storage device s at time t, respectively; D _n (t) is the load demand of load node n at time t;

For the power flow constraints of the power grid, the DC power flow equation that ignores the network loss is adopted. The common expressions of the DC power flow model are as follows:

Where: B _n,k is the imaginary part of the grid node admittance matrix; Δθ _ε,n,k (t) is the voltage phase angle difference between node n and node k of the system at time t; θ _ε,n (t), θ _{ε, k} (t) are the voltage phase angles of node n and node k of the system at time t, respectively; x _{n, k} are the line impedances of node n and node k;

The transmission line capacity constraint can be expressed as follows:

为连接系统节点n和节点k线路的最大传输容量；where:

is the maximum transmission capacity of the line connecting the system node n and node k;

Power system reserve demand constraints:

The expressions of equations (41) and (42) are suitable for different types of reserve requirements of the power system (such as 1-hour spinning reserve, 15-minute spinning reserve, non-spinning reserve, etc.). The present invention only considers the 15-minute spin-standby form.

和

分别为根据风电预测和负荷预测误差所得到电储能为系统提供上备用和下备用的值；

和

分别为电力系统上备用下备用的需求，可通过风电和负荷预测误差估计；α和β分别为满足系统上备用和下备用的置信度水平；In the formula: Pr( ) is the probability function;

and

are the values of the upper and lower backups provided by the electric energy storage for the system according to the wind power forecast and the load forecast error, respectively;

and

are the upper and lower backup requirements of the power system, which can be estimated by wind power and load forecast errors; α and β are the confidence levels for satisfying the upper and lower backup of the system, respectively;

2) Operational characteristic constraints of electric energy storage equipment

The operating characteristic constraints of the electric energy storage device are shown in equations (43)-(48).

分别为电储能设备s的充放电效率；

γ _s分别为电储能设备s的SOC上、下限系数；

为电储能设备s的额定容量；式(45)-(46)是电储能设备的充、放电功率约束；

分别为电储能设备s的最大充、放电功率；

分别为电储能设备s的充、放电工作状态，是0-1变量；式(47)是电储能设备工作状态约束；式(48)是电储能设备在考虑自放电情况下的充放电平衡约束；Equations (43)-(48) are the energy constraints of the electric energy storage device; E _s (t) is the electrical energy (SOC) stored by the electric energy storage device s at time t; δ _s is the self-consumption of the electric energy storage device s. loss factor in the case of discharge;

are the charge and discharge efficiencies of the electric energy storage device s, respectively;

γs are the upper and lower limit coefficients of the SOC of the electric energy storage device _s , respectively;

is the rated capacity of the electric energy storage device s; formulas (45)-(46) are the charge and discharge power constraints of the electric energy storage device;

are the maximum charging and discharging power of the electric energy storage device s, respectively;

are the charging and discharging working states of the electric energy storage device s respectively, which are 0-1 variables; Equation (47) is the working state constraint of the electric energy storage device; Equation (48) is the charging and discharging state of the electric energy storage device considering the self-discharge. Discharge balance constraints;

3) The energy storage backup service capacity must meet the following constraints:

和

分别为系统调用上备用和下备用时电储能设备的SOC值；where:

and

are the SOC values of the electric energy storage device when the system calls the upper backup and lower backup, respectively;

4) Unit characteristic constraints

Wind turbine output constraints

Relevant constraints such as output constraints, ramp rate constraints, and minimum start-stop time constraints of gas-fired and thermal power units are shown in the above related expressions.

S4: Solve the multi-resource optimal scheduling problem of the power system

The energy storage optimization configuration method established in the method proposed in the present invention considering the ramping ability and multi-stage state transition of gas and thermal power units can be linearized into a standard Mixed Integer Linear Programming (MILP) model, so the commercial software GAMS can be used to call CPLEX It is convenient to solve and obtain the power system dispatching decision-making scheme.

The following is a further description of the energy storage optimal configuration model proposed by the present invention that considers the climbing ability and multi-stage state transition of gas and thermal power units in combination with a numerical example:

The calculation example takes the modified PJM5 node system as an example for simulation analysis, as shown in Figure 4. The system has a total of 5 generators (gas unit and thermal power unit), and the relevant parameters of each generator are shown in Table 1. Table 2 is the operating parameters of the electric energy storage equipment, and Table 3 is the transmission line capacity. The values of VOLL and ^λw are 3000 yuan/MWh and 500 yuan/MWh, respectively. The confidence levels α and β are both 0.95. Consider a 24-hour day, with an interval of 1 hour each. Node 1 of the system is connected to a wind farm with an installed capacity of 600MW. The output and standby requirements of the wind farm in each scenario (S1-S5) are shown in Figure 5 and Figure 6, respectively, and the probability of each scenario is 23.22 %, 18.78%, 16.08%, 21.36% and 20.56%. The total system load is shown in Figure 7. The system load is located at nodes 2, 3, 4, and 3, which account for 41.5%, 30.3%, and 28.2% of the total load, respectively.

Table 1 Parameters of thermal power units

Table 2 Dispatching parameters of electric energy storage equipment

Table 3 shows the system indicators in different scenarios. It can be seen from the analysis results that the method proposed in the present invention is superior to other schemes in most system indexes because the ability of the electric energy storage device to provide system backup is considered. When the backup capacity provided by the electric energy storage device for the system is not considered, since only the traditional capacity can provide backup, the operating adjustment space of the unit is compressed, and a certain flexibility is sacrificed.

At the same time, the optimized configuration results also show that the configuration of energy storage equipment in the power system can reduce the demand for line expansion, and at the same time absorb more clean energy, especially to provide backup for the power system and provide more operating space for traditional units, enabling them to operate under optimal operating conditions.

Table 3 System indicators in different scenarios

Note: "-" indicates that the indicator is not applicable in this scenario

The present invention proposes an energy storage optimization configuration method that considers the ramping capability and multi-stage state transition of the gas and thermal power units of the system, and in a unified form, represents the mutual switching and transfer between the states of the gas-fired power unit and the thermal power unit during operation relation. At the same time, considering the operation and standby problem of the power system, a multi-resource scheduling model of the power system is proposed.

Taking into account that the energy storage and the unit jointly provide rotating backup for the system is more in line with the actual operation situation, more in line with the actual situation, and more practical.

A multi-resource scheduling model of the power system is proposed to realize the optimal scheduling of multiple resources of the power system and effectively reduce the waste of clean energy. Compared with the existing power system scheduling model or unit combination model, the proposed method is more realistic and more practical. It improves the accuracy of the thermal power unit operating characteristic model in the power system scheduling analysis, and makes the optimal allocation decision for peak shaving resources for the power system. Provides analytical tools with certain economic and environmental benefits.

The above are the preferred embodiments of the present invention, all changes made according to the technical solutions of the present invention, when the resulting functional effects do not exceed the scope of the technical solutions of the present invention, belong to the protection scope of the present invention.

Claims (3)

1. a method for optimizing the configuration of energy storage considering system gas and thermal power unit characteristics, is characterized in that, comprises the steps, S1. First, according to the historical data, predict the output of the new energy generator set, construct a typical scenario set of the output of the new energy generator set, and combine the load fluctuation characteristics to construct a load scenario set of the power system; S2. Analyze the operating characteristics of gas and thermal power units during the start-stop phase, establish state transition equations, clarify the transition conditions between states, and establish a state transition model for gas and thermal power units in the start-stop phases of operation. Transfer and switch between different states during the stop phase operation; S3: According to the system and operating parameters, on the basis of considering the wind power consumption target, with the goal of minimizing the relevant investment and total operating cost, construct an energy storage optimal configuration model that considers the climbing ability and multi-stage state transition of gas-fired and thermal power units ; S4: Solve the above power system energy storage optimization configuration problem, and obtain the power system energy storage optimization configuration scheme; The step S1 is specifically implemented as follows: The uncertainty of wind power output and load mainly considers the deviation of wind speed and load prediction, and it is considered that the respective deviations conform to the normal distribution; the true values of wind speed and load are expressed by the sum of the predicted expected value and the predicted error; the form is as follows:

where v(t) and _PL (t) are the actual values of wind speed and load, respectively;

are the forecast expected values of wind speed and load, respectively; e _v (t) and e _L (t) are the forecast errors of wind speed and load, respectively, both of which obey the probability distribution; The wind power output is calculated according to the following formula:

In the formula: P(v) is the output of the wind turbine at the wind speed v; v is the wind speed; v _in is the cut-in wind speed of the wind turbine; v _r is the rated power wind speed of the wind turbine; v _out is the cut-in wind speed of the wind turbine. wind speed; f(v) is the function of the relationship between the output power of the wind turbine and the wind speed when the wind speed is between v _in and v _r ; P _max is the rated power of the wind turbine; Combine wind power output and load to generate a set of power system operation scenarios; The step S2 is specifically implemented as follows: 1) Analyze the operating characteristics of the thermal power unit during the start-stop phase: the start-stop process of the thermal power unit needs to go through the process of increasing and decreasing the load; 2) Model the state of the thermal power unit, determine the number of operating states, and configure the 0-1 variables representing the state: According to the operating state characteristics of the thermal power unit during the start and stop phases, four 0-1 variables are introduced to represent the operating state of the unit: u _i (t) ,

Among them: u _i (t) indicates whether unit i is in the running and shutdown state at time t;

Indicates whether unit i is in a load-up state at time t;

Indicates whether unit i is in the state of accepting scheduling at time t;

Indicates whether unit i is in a reduced load state at time t; 3) Define the transition conditions between the states of the thermal power unit, and establish a state transition equation system: According to the operating state characteristics of the thermal power unit during the start and stop phases, the following state transition equations are introduced to represent the switch between the operating states of the unit;

y _i (t)-z _i (t)=u _i (t) (5)

y _i (t)+z _i (t)≤1 (9)

Equation (4) ensures that the unit can only be in a unique state each time; Equation (5)-Equation (12) are the state transition model and logic constraints representing the operating state of the unit; Equation (13)-Equation (16) represent the state transition The constraint relationship from one state to another state; the variables in the above formulas are all 0-1 variables, among which: y _i (t), z _i (t) are variables that control the start and stop states of the unit;

It is a variable that controls the unit to enter and exit the state of increasing the load;

Variables that control the unit to enter and exit the schedulable state;

It is a variable to control the unit entering and exiting the load reduction state;

Among them, M represents a large positive number, p _i (t) is the output of unit i at time t; Equation (17)-Equation (18) indicate that the output of the thermal power unit when it just enters the dispatchable state and the load reduction state must be is P _i , which ensures the connection between the states of the thermal power unit, and it is worth noting that the above formulas (17) and (18) are only applicable to thermal power units, not applicable to rapid start-up and shutdown units including gas-fired units; _Δpi (t)= _pi (t) _-pi (t-1) (19)

Equation (19)-Equation (21) are respectively the output change Δp _i (t) of the unit under the normal operating state of the system, and the output change when the upper spinning reserve is called

and the amount of output change when the lower spinning reserve is called

in,

and

is the value of upper spinning reserve and lower spinning reserve provided by the unit; 4) Write down the constraint equation of thermal power unit operating characteristics, and improve the start-stop stage model of thermal power unit:

Among them, Ru _i (t) and Rd _i (t) are the climbing and descending capabilities of the unit at time t, and can be calculated by the following formula;

Among them, I _thermal is the set of thermal power units; I _gas is the set of gas-fired units; RU _i and RD _i are the up-climbing and down-climbing capabilities of the unit in the dispatchable state;

are the climbing and descending capacities of the unit under load-up and load-down states, respectively, which can be calculated by the following formulas;

in,

and

is the duration of load raising and lowering;

Equation (26) is the maximum and minimum output of the system in normal operation, Equation (27) is the maximum and minimum output of the unit when the upper spinning reserve is called, and Equation (28) is the maximum and minimum output of the unit when the lower spinning reserve is called; Equation (29) ) is the constraint of the maximum and minimum upper and lower rotating reserve capacity of the unit; The minimum start and stop time constraints of the unit are as follows:

where T _i ^on (t) and T _i ^off (t) are the startup and shutdown times, respectively;

and

are the minimum startup and minimum downtime, respectively; In the case of piecewise linearization of the output curve of the unit, the power generation e _i (t) of the unit can be calculated by formula (31);

2. a kind of energy storage optimization configuration method considering system gas and thermal power unit characteristics according to claim 1, is characterized in that, described step S3 is specifically realized as follows: 1) The objective function of the energy storage optimization configuration model considering the ramping ability and multi-stage state transition of gas and thermal power units is constructed as follows:

In the formula: N is the set of power system network topology nodes; T is the set of scheduling time periods; I is the set of gas and thermal power units, i∈I; J is the set of wind turbines; S is the set of electric energy storage equipment, s∈S; E Wind output scene collection;

are the power generation cost, start-up cost, shutdown cost and backup service cost of gas-fired and thermal power unit i at time t, respectively;

The investment cost of electric energy storage equipment;

is the investment cost of the transmission line; pr _ε is the probability of occurrence of the wind power output scenario ε; VOLL and λ ^w are the loss of load cost and the unit wind curtailment penalty cost of power system dispatch; the last two parts of the above formula are the conditional risks of upper and lower backup value expectations; The power generation cost, start-up cost, shutdown cost and backup service cost of gas and thermal power unit i at time t are calculated by the following formulas (33)-(35); the investment and backup of electric energy storage equipment and transmission lines are calculated according to formula (36) Calculated with formula (37);

In the above formulas:

are the no-load cost and linear power generation cost of unit i, respectively;

are the starting, stopping, upper-backup, lower-backup service costs of a single unit or unit capacity, respectively; _cm and _cp are the investment costs required to equip unit capacity and unit power electric energy storage equipment, respectively; L is the transmission line set; c _line is the investment cost required to build a unit capacity line; P _l is the capacity expansion demand of line l; 2) Construct the optimal configuration model of energy storage considering the ramping ability and multi-stage state transition of gas and thermal power units. The constraints are as follows: 2.1) Constraints of power system operating characteristics Power system operating characteristic constraints, including power balance, DC power flow constraints, transmission line capacity constraints, and power system reserve demand constraints; ①The power balance constraint is expressed in the following form:

In the formula: N is the set of power system network topology nodes;

is the set of units at node n;

is the set of wind turbines at node n;

is the set of electrical energy storage devices at node n; p _i (t) is the output of unit i at time t;

is the dispatch value of wind farm j at time t;

are the charging and discharging power of the electric energy storage device s at time t, respectively; D _n (t) is the load demand of load node n at time t; ② DC power flow constraints, adopt the DC power flow equation that ignores the network loss, and the common expressions of the DC power flow model are as follows:

Where: B _n,k is the imaginary part of the grid node admittance matrix; Δθ _ε,n,k (t) is the voltage phase angle difference between node n and node k of the system at time t; θ _ε,n (t), θ _{ε, k} (t) are the voltage phase angles of node n and node k of the system at time t, respectively; x _{n, k} are the line impedances of node n and node k; ③ The capacity constraints of transmission lines are expressed as follows:

where:

is the maximum transmission capacity of the line connecting the system node n and node k; ④ Reserve demand constraints of the power system: The expressions of equations (41) and (42) are applicable to different types of reserve demands of the power system:

In the formula: Pr( ) is the probability function;

and

are the values of the upper and lower backups provided by the electric energy storage for the system according to the wind power forecast and the load forecast error, respectively;

and

are the upper and lower backup requirements of the power system, estimated by wind power and load forecast errors; α and β are the confidence levels for satisfying the upper and lower backup of the system, respectively; 2.2) Operating characteristic constraints of electric energy storage equipment The operating characteristic constraints of electric energy storage equipment are shown in equations (43)-(48):

Equations (43)-(48) are the energy constraints of the electric energy storage device; E _s (t) is the electric energy stored by the electric energy storage device s at time t; δ _s is the self-discharge condition of the electric energy storage device s loss factor;

are the charge and discharge efficiencies of the electric energy storage device s, respectively;

γs are the upper and lower limit coefficients of the SOC of the electric energy storage device _s , respectively;

is the rated capacity of the electric energy storage device s; formulas (45)-(46) are the charge and discharge power constraints of the electric energy storage device;

are the maximum charging and discharging power of the electric energy storage device s, respectively;

are the charging and discharging working states of the electric energy storage device s respectively, which are 0-1 variables; Equation (47) is the working state constraint of the electric energy storage device; Equation (48) is the charging and discharging state of the electric energy storage device considering the self-discharge. Discharge balance constraints; 2.3) Reserve service capacity of energy storage The energy storage backup service capacity must meet the following constraints:

where:

and

are the SOC values of the electric energy storage device when the system calls the upper backup and lower backup, respectively; 2.4) Output constraints of wind turbines The output constraints of the wind turbine are as follows:

where:

is the output value of wind farm j at time t; 3. a kind of energy storage optimization configuration method considering system gas and thermal power unit characteristics according to claim 1 and 2, it is characterized in that, in described step S4, will establish considering gas and thermal power unit climbing ability and multiple. The energy storage optimization configuration method of stage state transition is linearized into a standard mixed integer linear programming model, and then the commercial software GAMS is used to call CPLEX to facilitate the solution, and the power system scheduling decision-making scheme is obtained.

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