CN112053035A

CN112053035A - Power transmission channel and energy storage joint planning method considering economy and flexibility

Info

Publication number: CN112053035A
Application number: CN202010803123.4A
Authority: CN
Inventors: 游广增; 李玲芳; 甘霖; 李文云; 朱涛; 朱欣春
Original assignee: Yunnan Power Grid Co Ltd
Current assignee: Yunnan Power Grid Co Ltd
Priority date: 2020-08-11
Filing date: 2020-08-11
Publication date: 2020-12-08
Anticipated expiration: 2040-08-11
Also published as: CN112053035B

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 deal with environmental deterioration and exhaustion of fossil energy, large-scale integration 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 the 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 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.

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:

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;

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;

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:

in the formula:

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 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:

in the formula, P_LmaxIs 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(t₁),flex_line,s(t₂),…,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_totalFLEX (flexibility index of power transmission channel)_line(ii) a Wherein the total cost C of the planning scheme is_totalIncluding equivalent year construction and maintenance cost C_conAnd running cost C_oper(ii) a The upper layer planning model aims at:

F＝min{F₁,F₂} (9)

where s is the lower randomly running scene, psi_sThe occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c_oper,sAnd FLEX_line,sThe 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, which is the flexible resource set, x_iBuilding capacities for the ith flexible resource, c_iAs unit construction cost, Z_iA 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,sThe minimum is an optimization target; annual operating costs C_oper,sOperating cost C of thermal power generating unit under random scenes_G,sEnergy storage operation cost C_E,sDelivery cost C_out,sAnd a penalty cost C_penalty,sForming; lower floor transportThe objective function of the line 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

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_gThe 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

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_eFor energy storage charge-discharge cost coefficient, d_eminThe 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

κ_outFor 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

The penalty cost comprises a renewable energy abandon penalty cost and a load loss penalty cost; kappa_r,κ_lRespectively, 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,sAnd (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,minAnd x_i,maxRespectively 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,maxAn upper limit of the cost of construction and maintenance for an equivalent year;

(3) constraint of renewable energy utilization

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;_Ris 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_LmaxFor 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

In the formula, P_gmin,P_gmaxThe upper limit and the lower limit of the output power R of the thermal power generating unit g respectively_gG 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 (22)

In the formula, P_emin,P_emaxRespectively representing the upper and lower limits of the output power of the stored energy e;

(4) energy storage capacity constraint

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_eTo store the capacity of e, eta_eFor efficiency of charging and discharging, Soc_emin,Soc_emaxThe 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 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.

The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the joint planning method for power transmission channel and energy storage 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 combined planning system for power transmission channels and energy storage, which considers 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:

the specific steps of the step (1) comprise:

in the formula:

flex_line,s(t)＝max{flex_up,s(t),flex_down,s(t)} (30)

FLEX_line,s＝max{flex_line,s(t₁),flex_line,s(t₂),…,flex_line,s(t_n)} (31)。

The specific steps of the step (2) comprise:

F＝min{F₁,F₂} (32)

where s is the lower randomly running scene, psi_sIs the probability of occurrence of scene S, S isA lower-layer operation scene set; c_oper,sAnd FLEX_line,sThe 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, which is the flexible resource set, x_iBuilding capacities for the ith flexible resource, c_iAs unit construction cost, Z_iA 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,sThe minimum is an optimization target; annual operating costs C_oper,sOperating cost C of thermal power generating unit under random scenes_G,sEnergy storage operation cost C_E,sDelivery cost C_out,sAnd a penalty cost C_penalty,sForming; 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

(2) cost of stored energy running premium C_E,s

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_eFor energy storage charge-discharge cost coefficient, d_eminFor storing energy and naturally depreciating cost, when charging and discharging cost is lower than natural costWhen the depreciation cost is higher than the natural depreciation cost, the energy storage operation cost is the difference between the two costs;

(3) external grid power generation cost C_out,s

(4) penalty cost C_penalty,s

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)

(2) construction cost constraints

0≤C_con≤C_con,max (41)

(3) constraint 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)

(2) thermal power unit output constraint

(3) energy storage output restraint

P_emin≤P_e,s(t)≤P_emax (45)

(4) energy storage capacity constraint

In the formula, Soc_e,s(t) is energy storage at time t under random scene se state of charge, Q_eTo store the capacity of e, eta_eFor efficiency of charging and discharging, Soc_emin,Soc_emaxThe 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 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.

In the embodiment of the present invention, the 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 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.

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 may be embodied in the form of a software product, which is stored in a storage medium and includes 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

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:

in the formula:

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:

in the formula, P_LmaxIs the maximum transmission capacity of the transmission channel. Transmission channel up-regulation flexibility index flex_up,sThe physical meaning of (t) is the ability of the line to deliver renewable energy output power to the main network when the flexibility supply for up-regulation of the sub-grid cannot meet the flexibility demand for up-regulation; flexibility index flex is down regulated to transmission channel_down,sThe 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,sComprises the following steps:

flex_line,s(t)＝max{flex_up,s(t),flex_down,s(t)} (53)

FLEX_line,s＝max{flex_line,s(t₁),flex_line,s(t₂),…,flex_line,s(t_n)} (54)

step (2), based on the flexibility indexes provided in the step (1), a multi-objective storage and transmission double-layer planning model 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 objectives, and system structure parameters are determined; and 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 an optimal energy storage and thermal power generating unit control method, and returns the system operation parameters 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 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_totalFLEX (flexibility index of power transmission channel)_line. Wherein the total cost C of the planning scheme is_totalIncluding equivalent year construction and maintenance cost C_conAnd running cost C_operTwo parts. The upper layer planning model aims at:

F＝min{F₁,F₂} (55)

where s is the lower layer operational scene, psi_sThe occurrence probability of a scene S is set, and S is a lower-layer operation scene set; c_oper,sAnd FLEX_line,sThe operation cost and flexibility indexes of the planning scheme under the scene s; r is the discount rate, n is the engineering economic applicable year, K is the engineering fixed operation rate, which is the flexible resource set, x_iBuilding capacities for the ith flexible resource, c_iAs unit construction cost, Z_iThe decision variable is 0-1, 0 indicates that such flexible resource is not built, and 1 indicates that such flexible resource is built.

The formula (9) is an upper-layer planning model objective function, the formula (10) is a specific expression of each objective, and the formula (11) is the equivalent year construction and maintenance cost C_conAnd (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,minAnd x_i,maxAnd 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,maxThe upper limit of the cost for equivalent year construction and maintenance.

(3) Constraint 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,sThe minimum is an optimization goal. Annual operating costs C_oper,sOperating cost C of thermal power generating unit under various scenes_G,sEnergy storage running costC_E,sDelivery cost C_out,sPenalty cost C_penalty,sAnd (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

In the formula, P_g,s(t) is 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_gThe coefficient is the cost coefficient of the thermal power generating unit.

(2) Cost of stored energy running premium C_E,s

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_eFor energy storage charge-discharge cost coefficient, d_eminThe 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

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_outFor the cost coefficient of the outgoing power, P_out,s(t) is the output at time t under random scene sThe electric channel transmits power, and the system transmits the power to an external power grid to be positive, otherwise, the power is negative.

(4) Penalty cost C_penalty,s

The penalty cost comprises two parts of renewable energy abandonment penalty cost and load loss penalty cost. Kappa_r,κ_lRespectively, 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,sAnd (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 capacity constraints for power transmission channels

-P_Lmax≤P_L,s(t)≤P_Lmax (66)

In the formula, P_LmaxThe upper limit of the transmission capacity of the power transmission channel.

(2) Thermal power unit output constraint

In the formula, P_gmin,P_gmaxRespectively the upper and lower limits of the output power of the thermal power generating unit g, R_gAnd 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_emaxRespectively an upper limit and a lower limit of the output power of the stored energy e.

(4) Energy storage capacity constraint

In the formula, Soc_e,s(t) is the state of charge of the stored energy e at time t, Q_eTo store the capacity of e, eta_eFor efficiency of charging and discharging, Soc_emin,Soc_emaxAnd 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. 180MW, 100MW photovoltaic installation and 50MW thermal power installation are installed to the newly-increased wind-powered electricity generation field. At the moment, the capacity of a power transmission channel needs to be improved to enhance the clean energy consumption capability of the system, the punishment cost coefficient of abandoning renewable energy is set to be 9.67$/MW, the punishment cost coefficient of abandoning load is set to be 20.45$/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/($·(MW²·h)^-1)	0.062
P_gmin/MW	10	b_g/($·(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 the economic planning has certain punishment cost, 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 conventional economic planning is difficult to control, and planning schemes often leave less margin to cope with uncertain fluctuations in renewable energy sources when achieving the minimum economic cost. 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

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, essential 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 described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims

1. A power transmission channel and energy storage joint planning method considering economy and flexibility is characterized by comprising the following steps:

2. The combined economic and flexibility power transmission channel and energy storage planning method according to claim 1, wherein the concrete steps of step (1) include:

in the formula:

flex_line,s(t)＝max{flex_up,s(t),flex_down,s(t)} (7)

3. 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:

F＝min{F₁,F₂} (9)

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

(2) cost of stored energy running premium C_E,s

(3) external grid power generation cost C_out,s

(4) penalty cost C_penalty,s

4. The economic and flexibility considered power transmission channel and energy storage joint planning method according to claim 3, characterized in that the upper layer planning model constraints are as follows:

(1) flexible resource construction capacity constraints

x_i,min≤x_i≤x_i,max (17)

(2) construction cost constraints

0≤C_con≤C_con,max (18)

(3) constraint of renewable energy utilization

5. A combined economic and flexibility considered power transmission channel and energy storage planning method according to claim 3, characterized in that the lower operating model constraints are:

(1) transmission capacity constraints for power transmission channels

-P_Lmax≤P_L,s(t)≤P_Lmax (20)

(2) thermal power unit output constraint

In the formula, P_gmin,P_gmaxThe upper limit and the lower limit of the output power R of the thermal power generating unit g respectively_gG slope climbing rate, P, of thermal power generating unit_g,s(t) is the output power of the thermal power generating unit g at the moment t under the scene s, delta tIs a scheduling time interval;

(3) energy storage output restraint

P_emin≤P_e,s(t)≤P_emax (22)

(4) energy storage capacity constraint

6. The power transmission channel and energy storage joint planning method considering economy and flexibility as claimed in claim 3, characterized in that, after the Pareto optimal end face is obtained by solving with NSGAII optimization algorithm, the satisfaction degree of each Pareto optimal solution is calculated with fuzzy membership function, the optimal 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.

7. Considering economic nature and flexibility's transmission of electricity passageway and energy storage joint planning system, its characterized in that includes:

8. 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 6.

9. 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 6.