CN112053035B - Power transmission channel and energy storage joint planning method considering economy and flexibility - Google Patents

Power transmission channel and energy storage joint planning method considering economy and flexibility Download PDF

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CN112053035B
CN112053035B CN202010803123.4A CN202010803123A CN112053035B CN 112053035 B CN112053035 B CN 112053035B CN 202010803123 A CN202010803123 A CN 202010803123A CN 112053035 B CN112053035 B CN 112053035B
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游广增
李玲芳
甘霖
李文云
朱涛
朱欣春
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Abstract

The invention relates to a power transmission channel and energy storage joint planning method considering economy and flexibility, which adopts a multi-objective double-layer optimization model, takes the optimum economy and the optimum flexibility as targets for an upper layer model, and decides a route planning scheme; and the lower layer takes the operation economy as the optimum, decides the scheduling strategy of the power system and returns the result to the upper layer. The model is solved through an NSGAII optimization algorithm, and therefore multi-objective optimization of the model is achieved. The invention can effectively improve the flexibility of the power transmission channel and enhance the energy consumption capability of the system. Meanwhile, by introducing energy storage, the flexibility of a power transmission channel is improved, meanwhile, the cost of a planning scheme is guaranteed not to be greatly improved, and the obtained planning result has better economy and flexibility and is easy to popularize and apply.

Description

Power transmission channel and energy storage joint planning method considering economy and flexibility
Technical Field
The invention belongs to the technical field of planning and construction of renewable energy power systems, and particularly relates to a power transmission channel and energy storage combined planning method considering economy and flexibility.
Background
In order to cope with environmental deterioration and exhaustion of fossil energy, large-scale grid connection of renewable energy becomes a development direction of a power system. However, renewable energy has great uncertainty and is characterized by highly concentrated energy distribution and being far away from a load center, so that grid connection of renewable energy brings new challenges to power transmission channel planning of a power system. On the other hand, with the continuous development of the power grid technology, the application of the energy storage technology is gradually wide. The energy storage technology is applied to the side of the power grid, so that the output fluctuation of the renewable energy can be stabilized, the peak clipping and valley filling can be carried out, and the power transmission pressure of the power grid can be effectively relieved. Therefore, the method has important significance for researching the storage and transmission combined planning under the condition of high renewable energy permeability in order to relieve the contradiction between the renewable energy power generation and the power transmission and improve the renewable energy consumption rate.
At present, certain research achievements exist for planning energy storage and power transmission channels of renewable energy power systems at home and abroad. However, in the current research, economic indicators such as construction cost, operation cost and punishment cost of the power system are mostly used as optimization targets, and quantification of capability of the system for resisting uncertain events such as renewable energy fluctuation is lacked in an optimization model. Planning schemes often have less margin to cope with uncertain events while achieving economic optimality. The flexibility index can quantify the ability of the power system to economically and reliably cope with uncertain events such as renewable energy fluctuations. The development of flexible special planning has important significance for improving the utilization rate of renewable energy sources and enhancing the reliability of a high-proportion renewable energy power system. In 2018, IEA proposed a main idea of "flexibility is a new claim of power system" in annual energy prospect report, and the flexibility becomes another core characteristic attribute of power system besides safety, reliability and economy. At present, research on the flexibility of the power system by domestic and foreign research institutions is still in the initial stage, and mainly develops around the definition and quantitative evaluation of the basic concept, only a few documents consider the application of the flexibility in the power system planning, and most of the research is performed from the perspective of a power supply, and there is only a planning research on the flexibility index of a power transmission channel. Therefore, the flexibility planning of storage and transmission is carried out, the economical efficiency and the flexibility of the operation of the power grid are improved, the consumption capacity of the power system to renewable energy sources is enhanced, and great help is generated.
Disclosure of Invention
In order to overcome the defects, the invention provides a multi-target storage and transportation combined planning method considering flexibility and economy. Firstly, calculating the flexibility index of a power transmission channel, then establishing a storage and transmission double-layer planning model considering multiple targets based on the provided flexibility index, and solving the provided model through an NSGAII optimization algorithm, thereby realizing the optimization of the economy and the flexibility of the optimization model. The method provided by the invention can effectively improve the flexibility of the power transmission line, meet the grid-connected requirement of high-proportion renewable energy sources and enhance the consumption capability of the system to the renewable energy sources.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a power transmission channel and energy storage joint planning method considering economy and flexibility comprises the following steps:
step (1), calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel, and then calculating a flexibility index of the power transmission channel and a total flexibility index of the power transmission channel at the moment t under a scene s;
step (2), establishing a storage and transportation double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and takes economy and flexibility as optimization targets to carry out planning schemes, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, and iteratively solves to obtain the optimal planning scheme.
Further, it is preferable that the specific steps of step (1) include:
for any executed scheduling section t-1, the adjustable power requirement, namely the flexibility requirement, of the sub-grid for thermal power and energy storage at the next moment t is as follows:
Figure BDA0002628105620000021
Figure BDA0002628105620000022
in the formula: p load,s (t) is the load power of the sub-grid at the moment t under the random scene s, P r,s (t) the actual power generation amount of the r-th renewable energy source at the moment t under the random scene s; r is a system renewable energy set;
Figure BDA0002628105620000023
the flexible power demand of sub-grid up-regulation under the random scene s is equal to the difference value between the maximum possible load and the minimum renewable energy output of the system at the next moment;
Figure BDA0002628105620000024
the flexibility power demand is adjusted downwards for the sub-grid under the random scene s, and is equal to the difference value between the maximum renewable energy output and the minimum possible load of the system at the next moment;
the controllable unit flexibility power supply of the sub-grid at the next moment is as follows:
Figure BDA0002628105620000025
Figure BDA0002628105620000031
in the formula:
Figure BDA0002628105620000032
supplying flexible power for the system at the moment t under a random scene s; g is a system thermal power generating unit set, and E is an energy storage set; p gmax,s (t),P gmin,s (t) is the constraint of climbing rate and the constraint of upper and lower limits of unit output considered at t moment under random scene sObtaining the maximum and minimum output of the thermal power generating unit; p emax,s (t),P emin,s (t) the maximum charging and discharging power of the stored energy at the moment t under the random scene s, and the stored energy charging is specified to be positive and the discharging is specified to be negative;
flexibility index flex is adjusted downwards on power transmission channel at time t under random scene s up,s (t),flex down,s (t) is:
Figure BDA0002628105620000033
Figure BDA0002628105620000034
in the formula, P Lmax Is the maximum transmission capacity of the transmission channel; transmission channel up-regulation flexibility index flex up,s (t) the ability of the line to deliver renewable energy output power to the main network when the sub-grid up-regulation flexibility supply cannot meet the up-regulation flexibility requirement; flexibility index flex is down regulated to transmission channel down,s (t) the capacity of the line capable of transmitting power from the main network to meet the internal load demand of the system when the sub-grid down-regulation flexibility supply cannot meet the down-regulation flexibility demand;
calculating the flexibility index flex of the power transmission channel at the time t under the random scene s line,s (t) and total flexibility index FLEX of power transmission channel line,s ：
flex line,s (t)＝max{flex up,s (t),flex down,s (t)} (7)
FLEX line,s ＝max{flex line,s (t 1 ),flex line,s (t 2 ),…,flex line,s (t n )} (8)。
Further, it is preferable that the specific steps of step (2) include:
the optimization target of the upper-layer planning model is the total cost C of the planning scheme total FLEX (flexibility index of power transmission channel) line (ii) a Wherein, planning the total cost C of the scheme total Including equivalent year construction dimensionProtect cost C con And running cost C oper (ii) a The upper layer planning model aims at:
F＝min{F 1 ,F 2 } (9)
Figure BDA0002628105620000035
Figure BDA0002628105620000041
where s is the lower random operating scene, psi s The occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c oper,s And FLEX line,s The method comprises the following steps of (1) providing an index of operation cost and flexibility of a planning scheme under a random scene s; r is the discount rate, n is the engineering economy applicable year, K is the engineering fixed operation rate, gamma is the flexible resource set, x i Building capacities for the ith flexible resource, c i As unit construction cost, Z i A decision variable of 0 to 1, wherein 0 represents that the flexible resource is not built, and 1 represents that the flexible resource is built;
annual running cost C of lower-layer running model in random scenes oper,s The minimum is an optimization target; annual operating costs C oper,s Operating cost C of thermal power generating unit under random scenes G,s Energy storage operation cost C E,s Delivery cost C out,s And a penalty cost C penalty,s Forming; the objective function of the lower running model is:
f＝minC oper,s ＝minC G,s +C E,s +C out,s +C penalty,s (12)
the calculation formula of each operation cost is as follows:
(1) operating cost C of thermal power generating unit G,s
Figure BDA0002628105620000042
In the formula, P g,s (t) fire at time t under scene sThe output power of the motor group g; a is g ,b g ,c g The cost coefficient is the thermal power generating unit cost coefficient; t is lower layer operation simulation time;
(2) cost of stored energy running premium C E,s
Figure BDA0002628105620000043
In the formula, P e,s (t) storing energy charging and discharging power at the moment t under a random scene s, wherein the charging is specified to be positive and the discharging is specified to be negative; d e For the cost coefficient of energy storage charging and discharging, d emin The energy storage natural depreciation cost is set, when the charging and discharging cost is lower than the natural depreciation cost, the energy storage running cost is 0, and when the charging and discharging cost is higher than the natural depreciation cost, the energy storage running cost is the difference between the two costs;
(3) external grid power generation cost C out,s
Figure BDA0002628105620000044
κ out For the cost coefficient of the outgoing power, P out,s (t) in a random scene s, the power is transmitted by the power transmission channel at the time t, the power transmitted by the system to an external power grid is positive, and otherwise, the power is negative;
(4) penalty cost C penalty,s
Figure BDA0002628105620000051
The penalty cost comprises a renewable energy abandon penalty cost and a load loss penalty cost; kappa r ,κ l Respectively, renewable energy, loss load penalty cost coefficient, P l,s (t) is the power loss in random scene s, P r,s (t) and P rmax,s And (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the time t under the random scene s.
And then solving the double-layer planning model to obtain an optimal planning scheme.
Further, it is preferable that the upper layer planning model is constrained as follows:
(1) flexible resource construction capacity constraints
x i,min ≤x i ≤x i,max (17)
In the formula, x i,min And x i,max Respectively constructing upper and lower capacity limits for the ith flexible resource;
(2) construction cost constraints
0≤C con ≤C con,max (18)
In the formula, C con,max An upper limit of the cost of construction and maintenance for an equivalent year;
(3) constraint of renewable energy utilization
Figure BDA0002628105620000052
In the formula, P r,s (t) and P rmax,s (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the moment t under the random scene s; t is lower layer operation simulation time, and R is a system renewable energy set; epsilon R Is a threshold value of renewable energy utilization.
Further, it is preferable that the lower-layer operation model is constrained by:
(1) transmission capacity constraints for power transmission channels
-P Lmax ≤P L,s (t)≤P Lmax (20)
In the formula, P Lmax For transmission channel transmission capacity upper limit, P L,s (t) is line transmission power at time t under a random scene s;
(2) thermal power generating unit output constraint
Figure BDA0002628105620000053
In the formula, P gmin ,P gmax The upper limit and the lower limit of the output power R of the thermal power generating unit g respectively g G climbing for thermal power generating unitRate, P g,s (t) the output power of the thermal power generating unit g at the moment t under the scene s, and delta t is a scheduling time interval;
(3) energy storage output constraint
P emin ≤P e,s (t)≤P emax (22)
In the formula, P emin ,P emax Respectively representing the upper and lower limits of the output power of the stored energy e;
(4) energy storage capacity constraint
Figure BDA0002628105620000061
In the formula, Soc e,s (t) is the state of charge, Q, of the stored energy e at time t under the random scene s e To store the capacity of e, eta e For efficiency of charging and discharging, Soc emin ,Soc emax The upper and lower charge state limits of the stored energy e; Δ t is the scheduling time interval.
Further, preferably, after the Pareto optimal end face is obtained by solving through an NSGAII optimization algorithm, the satisfaction degree of each Pareto optimal solution is calculated through a fuzzy membership function, the optimization scheme with the maximum satisfaction degree is an optimal planning scheme, and the variable value of the individual is the current optimal decision value; the variable value comprises the configuration capacity of the power transmission channel and the configuration capacity of the energy storage device.
The invention simultaneously provides a power transmission channel and energy storage combined planning system considering economy and flexibility, which comprises:
the first processing module is used for calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel;
the second processing module is used for calculating a power transmission channel flexibility index and a power transmission channel total flexibility index at the moment t under a scene s;
the power transmission channel and energy storage combined planning and scheduling module is used for establishing a multi-target-considered storage and transmission double-layer planning model; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and takes economy and flexibility as optimization targets to carry out planning schemes, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, iteratively solves the calculation result to obtain an optimal planning scheme, and then plans and schedules according to the optimal planning scheme.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the power transmission channel and energy storage joint planning method considering economy and flexibility.
The invention further provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the above power transmission channel and energy storage joint planning method taking into account economy and flexibility.
The invention has no limit to the value of the discount rate and the fixed operation rate of the project, and the value range is 0.1-0.2 under the general condition.
Compared with the prior art, the invention has the beneficial effects that:
the invention firstly provides a power transmission channel flexibility index calculation method considering storage and transmission combined operation. And then, based on the provided flexibility index, a storage and output multi-target planning model considering economy and flexibility is constructed. The model is a double-layer optimization model, an upper planning layer determines a construction scheme, and a lower operation layer performs simulation operation on the planning scheme. And the upper layer calculates economic and flexibility indexes according to the operation result so as to optimize the planning scheme. And the solution of the optimal planning scheme is realized through continuous iteration of the upper layer and the lower layer. The invention can effectively improve the flexibility of the power transmission channel and enhance the energy consumption capability of the system. Meanwhile, by introducing energy storage, the flexibility of a power transmission channel is improved, the cost of a planning scheme is not greatly improved, and the obtained planning result has better economy and flexibility.
Drawings
FIG. 1 is a diagram of a planning model architecture;
FIG. 2 is a diagram of a power system architecture;
FIG. 3 is a set of exemplary operating scenarios for renewable energy sources;
FIG. 4 is a Pareto frontier chart of a flexible planning scheme;
FIG. 5 is a Pareto frontier chart of an economic planning scheme;
FIG. 6 is a diagram of planning total cost of a solution in a random scenario;
FIG. 7 is a diagram of a load rate and an energy storage state of charge variation of a power transmission channel for a planning scheme;
fig. 8 is a schematic structural diagram of a power transmission channel and energy storage combined planning system considering economy and flexibility;
fig. 9 is a schematic structural diagram of an electronic device according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples.
It will be appreciated by those skilled in the art that the following examples are illustrative of the invention only and should not be taken as limiting the scope of the invention. The examples do not specify particular techniques or conditions, and are performed according to the techniques or conditions described in the literature in the art or according to the product specifications. The materials, equipment and the like used are all conventional products which can be obtained by purchasing and are not indicated by manufacturers.
Example 1
A power transmission channel and energy storage joint planning method considering economy and flexibility is characterized by comprising the following steps:
step (1), calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel, and then calculating a flexibility index of the power transmission channel and a total flexibility index of the power transmission channel at the moment t under a scene s;
the specific steps of the step (1) comprise:
for any executed scheduling section t-1, the adjustable power requirement, namely the flexibility requirement of the sub-grid aiming at thermal power and energy storage at the next moment t is as follows:
Figure BDA0002628105620000081
Figure BDA0002628105620000082
in the formula: p load,s (t) is the load power of the sub-grid at the moment t under the random scene s, P r,s (t) the actual power generation amount of the r-th renewable energy source at the moment t under the random scene s; r is a system renewable energy set;
Figure BDA0002628105620000083
the flexible power demand of sub-grid up-regulation under the random scene s is equal to the difference value between the maximum possible load and the minimum renewable energy output of the system at the next moment;
Figure BDA0002628105620000084
the flexibility power demand is adjusted downwards for the sub-grid under the random scene s, and is equal to the difference value between the maximum renewable energy output and the minimum possible load of the system at the next moment;
the controllable unit flexibility power supply of the sub-grid at the next moment is as follows:
Figure BDA0002628105620000085
Figure BDA0002628105620000086
in the formula:
Figure BDA0002628105620000087
supplying flexible power for the system at the moment t under a random scene s; g is a system thermal power generating unit set, and E is an energy storage set; p is gmax,s (t),P gmin,s (t) maximum and minimum output of the thermal power generating unit are obtained by considering climbing rate constraint and unit output upper and lower limit constraint at t moment under a random scene s; p is emax,s (t),P emin,s (t) the maximum charging and discharging power of the stored energy at the moment t under the random scene s, and the stored energy charging is specified to be positive and the discharging is specified to be negative;
flexibility index flex is adjusted downwards on power transmission channel at time t under random scene s up,s (t),flex down,s (t) is:
Figure BDA0002628105620000091
Figure BDA0002628105620000092
in the formula, P Lmax Is the maximum transmission capacity of the transmission channel; transmission channel up-regulation flexibility index flex up,s (t) the ability of the line to deliver renewable energy output power to the main network when the sub-grid up-regulation flexibility supply cannot meet the up-regulation flexibility requirement; flexibility index flex is down regulated to transmission channel down,s (t) the capacity of the line capable of transmitting power from the main network to meet the internal load demand of the system when the sub-grid down-regulation flexibility supply cannot meet the down-regulation flexibility demand;
calculating the flexibility index flex of the power transmission channel at the time t under the random scene s line,s (t) and total flexibility index FLEX of power transmission channel line,s ：
flex line,s (t)＝max{flex up,s (t),flex down,s (t)} (30)
FLEX line,s ＝max{flex line,s (t 1 ),flex line,s (t 2 ),…,flex line,s (t n )} (31)。
Step (2), establishing a storage and transportation double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, and iteratively solves to obtain the optimal planning scheme.
The specific steps of the step (2) comprise:
the optimization target of the upper-layer planning model is the total cost C of the planning scheme total FLEX (flexibility index of power transmission channel) line (ii) a Wherein the total cost C of the planning scheme is total Including equivalent year construction and maintenance cost C con And operating cost C oper (ii) a The upper layer planning model aims at:
F＝min{F 1 ,F 2 } (32)
Figure BDA0002628105620000093
Figure BDA0002628105620000101
where s is the lower randomly running scene, psi s The occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c oper,s And FLEX line,s The method comprises the following steps of (1) providing an index of operation cost and flexibility of a planning scheme under a random scene s; r is the discount rate, n is the engineering economic applicable year, K is the engineering fixed operation rate, gamma is the flexible resource set, x i Building capacities for the ith flexible resource, c i As unit construction cost, Z i A decision variable of 0 to 1, wherein 0 represents that the flexible resource is not built, and 1 represents that the flexible resource is built;
annual running cost C of lower-layer running model in random scenes oper,s The minimum is an optimization target; annual operating costs C oper,s Operating cost C of thermal power generating unit under random scenes G,s Energy storage operation cost C E,s Delivery cost C out,s And a penalty cost C penalty,s Forming; the objective function of the lower running model is:
f＝minC oper,s ＝minC G,s +C E,s +C out,s +C penalty,s (35)
the calculation formula of each operation cost is as follows:
(1) operating cost C of thermal power generating unit G,s
Figure BDA0002628105620000102
In the formula, P g,s (t) the output power of the thermal power generating unit g at the moment t under the scene s; a is g ,b g ,c g The cost coefficient is the thermal power generating unit cost coefficient; t is lower layer operation simulation time;
(2) cost of stored energy running premium C E,s
Figure BDA0002628105620000103
In the formula, P e,s (t) storing energy charging and discharging power at the moment t under a random scene s, wherein the charging is specified to be positive and the discharging is specified to be negative; d e For energy storage charge-discharge cost coefficient, d emin The energy storage natural depreciation cost is set, when the charging and discharging cost is lower than the natural depreciation cost, the energy storage running cost is 0, and when the charging and discharging cost is higher than the natural depreciation cost, the energy storage running cost is the difference between the two costs;
(3) external grid power generation cost C out,s
Figure BDA0002628105620000104
κ out For the cost coefficient of the outgoing power, P out,s (t) power is transmitted to a power transmission channel at t moment under random scene s, and the system transmits power to the outsideThe network transmission power is positive, otherwise, the network transmission power is negative;
(4) penalty cost C penalty,s
Figure BDA0002628105620000111
The penalty cost comprises a renewable energy abandon penalty cost and a load loss penalty cost; kappa r ,κ l Respectively, renewable energy, loss load penalty cost coefficient, P l,s (t) is the power of the lost load in a random scene s, P r,s (t) and P rmax,s And (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the time t under the random scene s.
And then solving the double-layer planning model to obtain an optimal planning scheme.
Wherein, the upper layer planning model constraint is as follows:
(1) flexible resource construction capacity constraints
x i,min ≤x i ≤x i,max (40)
In the formula, x i,min And x i,max Respectively constructing upper and lower capacity limits for the ith flexible resource;
(2) construction cost constraints
0≤C con ≤C con,max (41)
In the formula, C con,max An upper limit of the cost of construction and maintenance for an equivalent year;
(3) constraint of renewable energy utilization
Figure BDA0002628105620000112
In the formula, P r,s (t) and P rmax,s (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the moment t under the random scene s; t is lower layer operation simulation time, and R is a system renewable energy set; epsilon R Is a threshold value of renewable energy utilization.
The lower run model constraints are:
(1) transmission capacity constraints for power transmission channels
-P Lmax ≤P L,s (t)≤P Lmax (43)
In the formula, P Lmax For transmission channel transmission capacity upper limit, P L,s (t) is line transmission power at time t under a random scene s;
(2) thermal power unit output constraint
Figure BDA0002628105620000113
In the formula, P gmin ,P gmax The upper limit and the lower limit of the output power of the thermal power generating unit g, R g G slope climbing rate, P, of thermal power generating unit g,s (t) the output power of the thermal power generating unit g at the moment t under the scene s, and delta t is a scheduling time interval;
(3) energy storage output restraint
P emin ≤P e,s (t)≤P emax (45)
In the formula, P emin ,P emax Respectively representing the upper and lower limits of the output power of the stored energy e;
(4) energy storage capacity constraint
Figure BDA0002628105620000121
In the formula, Soc e,s (t) is the state of charge, Q, of the stored energy e at time t under a random scene s e To store the capacity of e, eta e For efficiency of charging and discharging, Soc emin ,Soc emax The upper and lower charge state limits of the stored energy e; Δ t is the scheduling time interval.
Preferably, after the optimal Pareto end face is obtained by solving through an NSGAII optimization algorithm, the satisfaction degree of each Pareto optimal solution is calculated through a fuzzy membership function, the optimization scheme with the maximum satisfaction degree is the optimal planning scheme, and the variable value of the individual is the current optimal decision value; the variable value comprises the configuration capacity of the power transmission channel and the configuration capacity of the energy storage device.
As shown in fig. 8, the system for jointly planning power transmission channels and energy storage considering economy and flexibility includes:
the first processing module 101 is configured to calculate a power transmission channel up-regulation flexibility index and a power transmission channel down-regulation flexibility index;
the second processing module 102 is configured to calculate a flexibility index of a power transmission channel and a total flexibility index of the power transmission channel at time t in a scene s;
the power transmission channel and energy storage combined planning and scheduling module 103 is used for establishing a multi-objective storage and transmission double-layer planning model; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and takes economy and flexibility as optimization targets to carry out planning schemes, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, iteratively solves the calculation result to obtain an optimal planning scheme, and then plans and schedules according to the optimal planning scheme.
In the embodiment of the present invention, a first processing module 101 calculates a power transmission channel up-regulation flexibility index and a power transmission channel down-regulation flexibility index; the second processing module 102 calculates a flexibility index of a power transmission channel and a total flexibility index of the power transmission channel at the moment t under the scene s; the power transmission channel and energy storage combined planning and scheduling module 103 establishes a storage and transmission double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, iteratively solves the calculation result to obtain an optimal planning scheme, and then plans and schedules according to the optimal planning scheme.
According to the power transmission channel and energy storage combined planning system considering the economy and the flexibility, which is provided by the embodiment of the invention, the flexibility of the power transmission channel can be effectively improved, the on-site energy consumption capability of the system is enhanced, and the obtained planning result has better economy and flexibility and is easy to popularize and apply.
The system provided by the embodiment of the present invention is used for executing the above method embodiments, and for details of the process and the details, reference is made to the above embodiments, which are not described herein again.
Fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and referring to fig. 9, the electronic device may include: a processor (processor)201, a communication Interface (communication Interface)202, a memory (memory)203 and a communication bus 204, wherein the processor 201, the communication Interface 202 and the memory 203 complete communication with each other through the communication bus 204. The processor 201 may call logic instructions in the memory 203 to perform the following method: calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel, and then calculating a flexibility index of the power transmission channel and a total flexibility index of the power transmission channel at the moment t under a scene s; establishing a storage and transportation double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, and iteratively solves to obtain the optimal planning scheme.
In addition, the logic instructions in the memory 203 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
On the other hand, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, is implemented to perform the power transmission channel and energy storage joint planning method considering economy and flexibility provided in the foregoing embodiments, for example, the method includes calculating a power transmission channel up-regulation flexibility index and a power transmission channel down-regulation flexibility index, and then calculating a power transmission channel flexibility index and a power transmission channel total flexibility index at time t in a scene s; establishing a storage and transportation double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, and iteratively solves to obtain the optimal planning scheme.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Examples of the applications
A power transmission channel and energy storage joint planning method considering economy and flexibility comprises the following steps:
the invention provides an index calculation method aiming at the flexibility of a power transmission channel, so as to provide a basis for the storage and transmission combined planning of a power system.
For the provided flexibility index, the method is divided into a power transmission channel up-regulation flexibility index and a power transmission channel down-regulation flexibility index. For any executed scheduling section t-1, the adjustable power requirement, namely the flexibility requirement, of the sub-grid for thermal power and energy storage at the next moment t is as follows:
Figure BDA0002628105620000151
Figure BDA0002628105620000152
in the formula: p is load,s (t) is the load power of the sub-grid at time t under random scene s, P r,s (t) the actual power generation amount of the r-th renewable energy source at the moment t under the random scene s; r is a system renewable energy set;
Figure BDA0002628105620000153
the flexible power demand of sub-grid up-regulation under the random scene s is equal to the difference value between the maximum possible load and the minimum renewable energy output of the system at the next moment;
Figure BDA0002628105620000154
the flexibility power demand is adjusted downwards for the sub-grid under the random scene s, and is equal to the difference value between the maximum renewable energy output and the minimum possible load of the system at the next moment;
the controllable unit flexibility power supply of the sub-grid at the next moment is as follows:
Figure BDA0002628105620000155
Figure BDA0002628105620000156
in the formula:
Figure BDA0002628105620000157
supplying flexible power for the system at the moment t under a random scene s; g is a system thermal power generating unit set, and E is an energy storage set; p gmax,s (t),P gmin,s (t) maximum and minimum thermal power generating units are obtained by considering climbing rate constraint and unit output upper and lower limit constraint at t moment under a random scene s; p emax,s (t),P emin,s (t) the maximum charging and discharging power of the stored energy at the moment t under the random scene s, and the stored energy charging is specified to be positive and the discharging is specified to be negative;
therefore, the flexibility index flex is adjusted downwards on the power transmission channel at the moment t under the scene s up,s (t),flex down,s (t) is:
Figure BDA0002628105620000158
Figure BDA0002628105620000159
in the formula, P Lmax Is the maximum transmission capacity of the transmission channel. Transmission channel up-regulation flexibility index flex up,s The physical meaning of (t) is the capacity that the line can transmit renewable energy output power to the main network when the flexibility supply of the up-regulation of the sub-grid cannot meet the requirement of the flexibility of the up-regulation; flexibility index flex is down regulated to transmission channel down,s The physical meaning of (t) is the capability of the line to transmit power from the main network to meet the internal load requirement of the system when the sub-grid down-regulation flexibility supply cannot meet the down-regulation flexibility requirement; the stronger the power transmission capability of the power transmission channel is, the smaller the up-down flexibility index is, and the better the flexibility of the power transmission channel is.
Finally, the flexibility index flex of the power transmission channel at the moment t under the scene s line,s (t) and total flexibility index FLEX of power transmission channel line,s Comprises the following steps:
flex line,s (t)＝max{flex up,s (t),flex down,s (t)} (53)
FLEX line,s ＝max{flex line,s (t 1 ),flex line,s (t 2 ),…,flex line,s (t n )} (54)
step (2), based on the flexibility indexes provided in the step (1), a storage and transmission double-layer planning model considering multiple targets is established, the upper layer is a storage and transmission planning layer, the upper layer takes construction capacities of two flexibility resources of energy storage and power transmission lines as decision variables, planning schemes are carried out by taking economy and flexibility as optimization targets, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target, so as to obtain the optimal energy storage and thermal power unit control method, and system operation parameters are returned to the upper layer. And the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, and optimizes the planning scheme according to the calculation result. The model realizes the iteration between the upper layer and the lower layer in the process of continuously repeating the steps. The model realizes the optimization solution of the planning scheme based on the iterative process. And solving the model to obtain the optimal planning and construction scheme of the power grid.
The optimization target of the upper-layer planning model is the total cost C of the planning scheme total FLEX (flexibility index of power transmission channel) line . Wherein, planning the total cost C of the scheme total Including equivalent year construction and maintenance cost C con And running cost C oper Two parts. The upper layer planning model aims at:
F＝min{F 1 ,F 2 } (55)
Figure BDA0002628105620000161
Figure BDA0002628105620000162
where s is the lower layer operational scene, psi s The occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c oper,s And FLEX line,s The operation cost and flexibility indexes of the planning scheme under the scene s; r is the discount rate, n is the engineering economy applicable year, K is the engineering fixed operation rate, gamma is the flexible resource set, x i Building capacities for the ith flexible resource, c i As unit construction cost, Z i The decision variable is 0-1, 0 indicates that such flexible resource is not built, and 1 indicates that such flexible resource is built.
Equation (9) is an upper layer planning model objective function, equation (10) is a specific expression of each objective, and equation (11) is the equivalent year construction and maintenance cost C con And (4) calculating a formula.
The upper layer planning model constraints are as follows:
(1) flexible resource construction capacity constraints
x i,min ≤x i ≤x i,max (58)
In the formula, x i,min And x i,max And respectively building capacity upper and lower limits for the ith flexible resource.
(2) Construction cost constraints
0≤C con ≤C con,max (59)
In the formula, C con,max The upper limit of the cost for equivalent year construction and maintenance.
(3) Constraint of renewable energy utilization
Figure BDA0002628105620000171
In the formula, P r,s (t) and P rmax,s (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the moment t under the random scene s; t is lower layer operation simulation time, and R is a system renewable energy set; epsilon R Is a threshold value of renewable energy utilization.
The lower layer operates at the annual cost C of each scene because the fundamental purpose of improving the flexibility of the power transmission channel is to enhance the consumption capacity of the system on renewable energy sources oper,s The minimum is an optimization goal. Annual operating costs C oper,s Operating cost C of thermal power generating unit under each scene G,s Energy storage running cost C E,s Delivery cost C out,s Penalty cost C penalty,s And (4) forming. The objective function of the lower running model is:
f＝minC oper,s ＝minC G,s +C E,s +C out,s +C penalty,s (61)
the calculation formula of each operation cost is as follows:
(1) operating cost C of thermal power generating unit G,s
Figure BDA0002628105620000172
In the formula, P g,s (t) the output power of the thermal power generating unit g at the moment t under the random scene s; a is g ,b g ,c g The coefficient is the cost coefficient of the thermal power generating unit.
(2) Cost of stored energy running premium C E,s
Figure BDA0002628105620000181
In the formula, P e,s (t) storing energy charging and discharging power at the moment t under a random scene s, wherein the charging is specified to be positive and the discharging is specified to be negative; d e For energy storage charge-discharge cost coefficient, d emin The energy storage natural depreciation cost is set as the difference between the energy storage running cost and the energy storage running cost when the charging and discharging cost is lower than the natural depreciation cost and the energy storage running cost is 0 when the charging and discharging cost is higher than the natural depreciation cost.
(3) External grid power generation cost C out,s
Figure BDA0002628105620000182
When the output power of the generator in the system is not enough to meet the load requirement of the system, an external power grid is required to transmit power to the system through a power transmission channel, so that certain cost is generated. Kappa out For the cost coefficient of the outgoing power, P out,s And (t) the power is transmitted by the power transmission channel at the moment t under the random scene s, the power transmitted by the system to the external power grid is positive, and otherwise, the power is negative.
(4) Penalty cost C penalty,s
Figure BDA0002628105620000183
The penalty cost comprises two parts of renewable energy abandonment penalty cost and load loss penalty cost. Kappa r ,κ l Punishment for renewable energy and loss of load respectivelyCoefficient of merit, P l,s (t) is the power loss in random scene s, P r,s (t) and P rmax,s And (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the time t under the random scene s.
The lower run model constraints are:
(1) transmission channel transmission capacity constraints
-P Lmax ≤P L,s (t)≤P Lmax (66)
In the formula, P Lmax The upper limit of the transmission capacity of the power transmission channel.
(2) Thermal power unit output constraint
Figure BDA0002628105620000184
In the formula, P gmin ,P gmax Respectively the upper and lower limits of the output power of the thermal power generating unit g, R g And the g climbing rate of the thermal power generating unit is shown, and delta t is a scheduling time interval.
(3) Energy storage output restraint
P emin ≤P e,s (t)≤P emax (68)
In the formula, P emin ,P emax Respectively an upper limit and a lower limit of the output power of the stored energy e.
(4) Energy storage capacity constraint
Figure BDA0002628105620000191
In the formula, Soc e,s (t) the state of charge of the stored energy e at time t, Q e To store the capacity of e, eta e For efficiency of charging and discharging, Soc emin ,Soc emax And the upper and lower charge state limits of the energy storage e are shown, and delta t is a scheduling time interval.
And solving the multi-target model by adopting an NSGAII optimization algorithm to obtain Pareto optimal end faces, and calculating the satisfaction degree of each Pareto optimal solution by adopting a fuzzy membership function. The optimization scheme with the maximum satisfaction degree is the optimal planning scheme, and the variable value of the individual is the current optimal decision value. The variable value comprises the configuration capacity of the power transmission channel and the configuration capacity of the energy storage device.
In order to verify the effectiveness of the invention, in a power system containing wind power, photovoltaic and thermal power as shown in fig. 2, the flexibility planning of a power transmission channel is performed by taking energy storage and lines as flexible resources.
The capacity of an original power transmission channel of the sub-grid is 70MW, the wind power installation capacity is 140MW, the maximum load is 100MW, and no energy storage device is arranged. Suppose that a wind power plant, a photovoltaic power plant and a thermal power plant are additionally arranged on a sub-grid in a certain planning level year in the future. The newly-increased wind-powered electricity generation field installation 180MW, photovoltaic installation 100MW, thermal power installation 50 MW. At the moment, the capacity of a power transmission channel needs to be improved to enhance the clean energy consumption capacity of the system, the punishment cost coefficient of abandoning the renewable energy is set to be 9.67$/MW, the punishment cost coefficient of abandoning the load is set to be 20.45$/MW, the power generation cost coefficient of an external power grid is set to be 11.2$/MW, and the system parameters are shown in tables 1 and 2.
TABLE 1 thermal power generating unit parameters
Parameter(s) Parameter(s)
P gmax /MW 50 a g /($·(MW 2 ·h) -1 ) 0.062
P gmin /MW 10 b g /($·(MW·h) -1 ) 2.1954
R g /MW 5 c g /($·h -1 ) 80
TABLE 2 energy storage parameters
Parameter(s) Parameter(s)
P emax /Q e 0.8 d e 0.05
P emin /Q e -0.8 d emin 5.32
Soc emax 1 η e 0.92
Soc emin 0.1
A set of typical operating scenarios for renewable energy sources is shown in fig. 3. For convenience of display, the renewable energy output and the load output are subjected to per unit treatment by taking the renewable energy output and the loading capacity and the maximum load as basic values. Setting the energy storage cost to be 60000$/MWh, the line construction cost to be 120000$/MW, the discount rate to be 0.1, the engineering service life to be 20 years and the lower-layer scheduling time to be 1 h. The population number is set as 100, the iteration is performed for 100 generations, and the Pareto front edge of the final planning result is shown as an 'x' type scheme set in fig. 4.
As can be seen from fig. 4, as the energy storage and line investment costs increase, the flexibility index of the power transmission channel gradually decreases, and the flexibility increases. In the upper diagram, the o-type scheme is set as a Pareto front edge obtained when no energy storage is built and only a line is built. It can be seen that energy storage and line construction are performed simultaneously, and compared with the construction of only lines, better flexibility can be obtained at the same economic cost. Or the planning model can reduce the economic cost of the planning scheme while meeting the flexibility of the system through the action of energy storage peak clipping and valley filling.
For comparison, the invention also performs the traditional planning only considering the economic index. Under the simulation operation scene set, the power transmission channel is planned with the investment cost and the operation cost as targets, and the Pareto front edge of the final planning result is shown in fig. 5.
The optimal solutions of the two planning schemes and their main indicators are shown in table 3. It can be seen that the annual operating cost of an economic planning scheme is higher than that of a flexible planning scheme. The analysis shows that the reason is that certain punishment cost exists in the economic planning, namely, the economic planning realizes the great reduction of the construction cost by allowing certain renewable energy sources and loads to be abandoned. Thus, economic planning greatly reduces the overall cost of the planning solution compared to flexible planning solutions. However, as mentioned above, the robustness of the conventional economic planning is difficult to control, and the planning scheme often has a small margin for coping with uncertain fluctuations of renewable energy sources when the minimum economic cost is achieved. The output of renewable energy sources of the scene set fluctuates uniformly within the range of [0,0.25], and 10 random scenes are regenerated, and the total cost of the two planning schemes is shown in fig. 6.
TABLE 3 optimal solution of planning scheme and its main indexes
Figure BDA0002628105620000201
As can be seen from fig. 6, in the newly generated 10 random scenarios, the total cost of the flexible planning is smaller than the economic planning. This is because conventional economic planning methods cannot measure the ability of the system to cope with uncertain events, and it is therefore difficult to control the margin left for the planning scheme. The obtained optimal scheme is often the optimal scheme under the scene as input data, once the retention margin is insufficient, the situation of index deterioration is easy to occur under other scenes, and due to the fact that the bearing capacity of the planning scheme on uncertain events can be accurately controlled, the stability of the optimization target can be always kept under other scenes.
Fig. 7 shows the load rate of the power transmission channel and the change of the energy storage state of charge of the two planning schemes in scene 1. Scene 1 belongs to the scene with the largest renewable energy power transmission demand, and it can be seen that the power transmission channel under the two planning schemes is fully loaded in most cases. This is mainly due to two reasons. One is that the planning scheme preferentially selects to transmit the output of the renewable energy source to the main network through the power transmission channel, but not to absorb the part of power through the energy storage, thereby causing the charging and discharging cost of the energy storage. Another is that when the power transmission channel is not fully loaded, the stored energy may be discharged at a premium cost of 0 to ensure that the state of charge is not too high.
At some point, when the capacity of the transmission channel is not enough to meet the transmission requirement, the stored energy will start to be charged. As can be seen from fig. 7(b), the energy storage state of charge of the flexible programming is at most 0.83, and in most cases below 0.6, which indicates that the flexible programming has more margin to balance the output fluctuation of the renewable energy. In the economic planning, the stored energy reaches a full load state quickly due to the small energy storage capacity, and if the transmission requirement of the renewable energy cannot be met at the moment, the condition of abandoning the renewable energy is generated.
The foregoing shows and describes the general principles, principal features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, and such changes and modifications are within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (8)

1. A power transmission channel and energy storage joint planning method considering economy and flexibility is characterized by comprising the following steps:
step (1), calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel, and then calculating a flexibility index of the power transmission channel and a total flexibility index of the power transmission channel at the moment t under a scene s;
step (2), establishing a storage and transportation double-layer planning model considering multiple targets; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, and iteratively solves to obtain an optimal planning scheme;
the specific steps of the step (1) comprise:
for any executed scheduling section t-1, the adjustable power requirement, namely the flexibility requirement, of the sub-grid for thermal power and energy storage at the next moment t is as follows:
Figure FDA0003619286690000011
Figure FDA0003619286690000012
in the formula: p load，s (t) is the load power of the sub-grid at time t under random scene s, P r，s (t) the actual power generation amount of the r-th renewable energy source at the moment t under the random scene s; r is a system renewable energy set;
Figure FDA0003619286690000013
the flexible power demand is adjusted upwards for the sub-grid under the random scene s, and is equal to the difference value between the maximum possible load of the system and the minimum renewable energy output at the next moment;
Figure FDA0003619286690000014
the flexibility power demand is adjusted downwards for the sub-grid under the random scene s, and is equal to the difference value between the maximum renewable energy output and the minimum possible load of the system at the next moment;
the controllable unit flexibility power supply of the sub-grid at the next moment is as follows:
Figure FDA0003619286690000015
Figure FDA0003619286690000021
in the formula:
Figure FDA0003619286690000022
supplying flexible power for the system at the moment t under the random scene s; g is a system thermal power generating unit set, and E is an energy storage set; p is gmax，s (t)，P gmin，s (t) maximum and minimum output of the thermal power generating unit are obtained by considering climbing rate constraint and unit output upper and lower limit constraint at t moment under a random scene s; p emax，s (t)，P emin，s (t) the maximum charging and discharging power of the stored energy at the moment t under the random scene s, and the stored energy charging is specified to be positive and the discharging is specified to be negative;
flexibility index flex is adjusted downwards on power transmission channel at time t under random scene s up，s (t)，flex down，s (t) is:
Figure FDA0003619286690000023
Figure FDA0003619286690000024
in the formula, P Lmax Is the maximum transmission capacity of the transmission channel; transmission channel up-regulation flexibility index flex up，s (t) the ability of the line to deliver renewable energy output power to the main network when the sub-grid up-regulation flexibility supply cannot meet the up-regulation flexibility requirement; flexibility index flex is down regulated to transmission channel down，s (t) the capacity of the line capable of transmitting power from the main network to meet the internal load demand of the system when the sub-grid down-regulation flexibility supply cannot meet the down-regulation flexibility demand;
calculating the flexibility index flex of the power transmission channel at the time t under the random scene s line，s (t) and total flexibility index FLEX of power transmission channel line，s ：
flex line，s (t)＝max{flex up，s (t)，flex down，s (t)} (7)
FLEX line，s ＝max{flex line，s (t 1 )，flex line，s (t 2 )，L，flex line，s (t n )} (8)。
2. The combined economic and flexibility power transmission channel and energy storage planning method according to claim 1, wherein the concrete steps of step (2) include:
the optimization target of the upper-layer planning model is the total cost C of the planning scheme total FLEX (flexibility index of power transmission channel) line (ii) a Wherein the total cost C of the planning scheme is total Including equivalent year construction and maintenance cost C con And running cost C oper (ii) a The upper layer planning model aims at:
F＝min{F 1 ，F 2 } (9)
Figure FDA0003619286690000031
Figure FDA0003619286690000032
where s is the lower randomly running scene, psi s The occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c oper，s And FLEX line，s Running cost and flexibility indexes of the planning scheme in the random scene s; r is the discount rate, n is the engineering economic applicable year, K is the engineering fixed operation rate, gamma is the flexible resource set, x i Building capacities for the ith flexible resource, c i As unit construction cost, Z i A decision variable of 0-1, 0 means that the species is not constructedFlexible resources, 1 denotes building such flexible resources;
annual running cost C of lower-layer running model in random scenes oper，s The minimum is an optimization target; annual operating costs C oper，s Operating cost C of thermal power generating unit under random scenes G，s Energy storage operation cost C E，s Delivery cost C out，s And a penalty cost C penalty，s Forming; the objective function of the lower running model is:
f＝min C oper，s ＝min(C G，s +C E，s +C out，s +C penalty，s ) (21)
the calculation formula of each operation cost is as follows:
(1) operating cost C of thermal power generating unit G，s
Figure FDA0003619286690000033
In the formula, P g，s (t) the output power of the thermal power generating unit g at the moment t under the scene s; a is g ，b g ，c g The cost coefficient of the thermal power generating unit is obtained; t is lower layer operation simulation time;
(2) cost of stored energy running premium C E，s
Figure FDA0003619286690000034
In the formula, P e，s (t) storing energy charging and discharging power at the moment t under a random scene s, wherein the charging is specified to be positive and the discharging is specified to be negative; d e For energy storage charge-discharge cost coefficient, d emin The energy storage natural depreciation cost is set, when the charging and discharging cost is lower than the natural depreciation cost, the energy storage running cost is 0, and when the charging and discharging cost is higher than the natural depreciation cost, the energy storage running cost is the difference between the two costs;
(3) external grid power generation cost C out，s
Figure FDA0003619286690000041
κ out For the cost coefficient of the outgoing power, P out，s (t) in a random scene s, the power is transmitted by the power transmission channel at the time t, the power transmitted by the system to an external power grid is positive, and otherwise, the power is negative;
(4) penalty cost C penalty，s
Figure FDA0003619286690000042
The penalty cost comprises a renewable energy abandon penalty cost and a load loss penalty cost; kappa r ，κ l Respectively, the cost coefficient of the renewable energy source and the loss load punishment, P l，s (t) is the power loss in random scene s, P r，s (t) and P rmax，s (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the moment t under the random scene s;
and then solving the double-layer planning model to obtain an optimal planning scheme.
3. The joint power transmission channel and energy storage planning method considering economy and flexibility as claimed in claim 1, wherein the upper layer planning model constraints are as follows:
(1) flexible resource construction capacity constraints
x i，min ≤x i ≤x i，max (12)
In the formula, x i，min And x i，max Respectively constructing upper and lower capacity limits for the ith flexible resource;
(2) construction cost constraints
0≤C con ≤C con，max (13)
In the formula, C con，max An upper limit of the cost of construction and maintenance for an equivalent year;
(3) constraint of renewable energy utilization
Figure FDA0003619286690000043
In the formula, P r，s (t) and P rmax，s (t) the actual power generation amount and the maximum power generation amount of the r-th renewable energy source at the moment t under the random scene s; t is lower layer operation simulation time, and R is a system renewable energy set; epsilon R Is a threshold value of renewable energy utilization.
4. The economic and flexibility considered power transmission channel and energy storage joint planning method according to claim 2, characterized in that the lower layer operation model constraints are:
(1) transmission capacity constraints for power transmission channels
-P Lmax ≤P L，s (t)≤P Lmax (26)
In the formula, P Lmax For transmission channel transmission capacity upper limit, P L，s (t) is line transmission power at time t under a random scene s;
(2) thermal power unit output constraint
Figure FDA0003619286690000051
In the formula, P gmin ，P gmax The upper limit and the lower limit of the output power R of the thermal power generating unit g respectively g G ramp rate, P, of thermal power generating unit g，s (t) the output power of the thermal power generating unit g at the moment t under the scene s, and delta t is a scheduling time interval;
(3) energy storage output restraint
P emin ≤P e，s (t)≤P emax (28)
In the formula, P emin ，P emax Respectively representing the upper and lower limits of the output power of the stored energy e;
(4) energy storage capacity constraint
Figure FDA0003619286690000052
In the formula, Soc e，s (t) is the state of charge, Q, of the stored energy e at time t under the random scene s e To store the capacity of e, eta e For efficiency of charging and discharging, Soc emin ，Soc emax The upper and lower charge state limits of the stored energy e; Δ t is the scheduling time interval.
5. The power transmission channel and energy storage joint planning method considering economy and flexibility as claimed in claim 2, characterized in that, the solution is performed by using NSGAII optimization algorithm, after the Pareto optimal front edge is obtained, the satisfaction degree of each Pareto optimal solution is calculated by using fuzzy membership function, the optimization scheme with the maximum satisfaction degree is the optimal planning scheme, and the variable value of the individual is the current optimal decision value; the variable value comprises the configuration capacity of the power transmission channel and the configuration capacity of the energy storage device.
6. The power transmission channel and energy storage joint planning system considering the economy and the flexibility is adopted by the power transmission channel and energy storage joint planning method considering the economy and the flexibility, which is characterized by comprising the following steps:
the first processing module is used for calculating an up-regulation flexibility index and a down-regulation flexibility index of a power transmission channel;
the second processing module is used for calculating a power transmission channel flexibility index and a power transmission channel total flexibility index at the moment t under the scene s;
the power transmission channel and energy storage combined planning and scheduling module is used for establishing a multi-target-considered storage and transmission double-layer planning model; the upper layer is a storage and transmission planning layer, the upper layer takes construction capacity of two flexible resources of energy storage and power transmission lines as decision variables, and an economic efficiency and flexibility as optimization targets to carry out planning scheme, and system structure parameters are determined; the lower layer is an operation simulation layer, the layer performs multi-scene operation simulation under the system structure determined by the upper layer by taking the optimal operation economy as a target to obtain an optimal energy storage and thermal power generating unit control method, and system operation parameters are returned to the upper layer; and the upper layer calculates the economic index and the flexibility index of the planning scheme according to the lower layer operation simulation parameters, optimizes the planning scheme according to the calculation result, iteratively solves the calculation result to obtain an optimal planning scheme, and then plans and schedules according to the optimal planning scheme.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for joint power transmission channel and energy storage planning in consideration of economy and flexibility as claimed in any one of claims 1 to 5.
8. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for joint planning of power transmission paths and energy storage considering economy and flexibility as claimed in any one of claims 1 to 5.
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