CN117422227B - Transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristic - Google Patents
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Abstract
The embodiment of the invention relates to a transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics. The method comprises the following steps: reading in relevant original data of a power system to be planned; constructing a double-sided energy storage model for decoupling real-time power balance constraint of a power transmission network and a power distribution network by utilizing the original data; a time-sharing consumption subsidy strategy for connecting the cooperative operation between a transmission network and a distribution network is formulated, and the strategy and a charge-discharge strategy of double-side energy storage are taken as a cooperative shared decision variable of the transmission network and the distribution network; combining the bilateral energy storage model and a shared decision variable to establish a transmission and distribution network bilateral energy storage collaborative planning model; and decomposing the transmission and distribution network of the established collaborative planning model, and then alternately and iteratively solving to obtain a transmission and distribution network double-side energy storage collaborative planning result. The method can well coordinate various resources of the transmission and distribution network under the coupling of source network charge storage, and improves the planning and running economy of the energy storage system.
Description
Technical Field
The embodiment of the invention relates to the technical field of power system planning, in particular to a transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics.
Background
With the large-scale grid connection of centralized and distributed new energy sources, the traditional power system evolves towards a high-proportion new energy source power system, but because wind power and photovoltaic are affected by climate, the intermittence and fluctuation of output of the power system can cause adverse effects on safe and stable operation of a power grid, in addition, the blockage of a new energy source sending channel and the reverse peak regulation characteristic of power generation can cause the generation of wind discarding and wind discarding light discarding phenomena, and technologies such as battery energy storage and water pumping energy storage are good countermeasures for solving the problem. In addition, management of a power transmission network and a power distribution network in a modern power system is separated for a long time, and under the background of rapid increase of new energy installation proportion, the management structure lacks an effective coordination mechanism, so that the problems of rising system operation cost, low utilization rate of an energy storage device and the like are caused, and therefore, collaborative planning and operation of the power transmission network and the power distribution network become hot spots of current research.
In the aspect of source-load coordination, a novel electricity price planning plan is provided by researches, the digestion capability of a distributed power generation device (Distributed Generation, which is called as DG hereinafter) is enhanced, the capacity of a power system is improved, and the coordination of active load response behaviors and the operation of the DG and a main network is considered by the researches, so that an index for evaluating the response behavior characteristics is provided. In the aspect of source storage coordination, a day-ahead optimization scheduling model for DG and energy storage is established by taking the power quality of a power distribution network as an optimization target, an active power and reactive power are provided for fitting an optimized tide model, the network loss and the power minimization of the power distribution network are taken as targets, and a method for coordinating work of a new energy station and matched energy storage is used for research, so that the permeability of wind power is improved. The coordination of the source network and the charge three-side resources is considered from the day-ahead optimization scheduling of the dynamic reconstruction of the grid, the DG and the active load, the coordination of the source and the charge is considered on the micro-grid model, and the active load, the DG and the energy storage are comprehensively considered to realize the running economy.
However, the following important challenges still remain in the field of collaborative planning of transmission and distribution networks:
1) Most of the current researches only consider scheduling operation, but planning is still less, or more simplification is carried out in collaborative planning research, so that the schedulable flexible resources are less, and the problems of low collaborative efficiency of transmission and distribution networks and high planning cost exist.
2) The energy storage technology at the power grid side in China and the like are initially large-scale, but the existing research about the application of energy storage to the collaborative planning of the power transmission and distribution network is still less, most of the planning of the power source of the power transmission and distribution network is still carried out separately, so that the cost waste is caused by the mismatching of the capacity of the power transmission network in the power source upgrading process, the flexible resources of the power distribution network cannot be effectively utilized by the power transmission network, and the problems that the energy storage capacity at the power transmission network side and the power distribution network side are difficult to reasonably optimize and configure and apply exist.
Disclosure of Invention
Based on the above situation of the prior art, an object of the embodiments of the present invention is to provide a method for collaborative planning of energy storage on both sides of a transmission network and a distribution network, which takes account of the coupling characteristics of the source network and the charge storage, and to build a planning model with better cost and more flexible resources in the field of collaborative optimization planning of the transmission network and the distribution network, and to take account of the coupling characteristics of the source network and the charge storage, so as to implement an energy storage planning method capable of cooperating the transmission network and the distribution network.
In order to achieve the above object, according to a first aspect of the present invention, there is provided a transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics, including the steps of:
s1: reading in relevant original data of a power system to be planned; the power system to be planned comprises a power transmission network and a power distribution network;
s2: constructing a double-sided energy storage model for decoupling real-time power balance constraint of a power transmission network and a power distribution network by utilizing the original data;
s3: a time-sharing consumption subsidy strategy for connecting the cooperative operation between a transmission network and a distribution network is formulated, and the strategy and a charge-discharge strategy of double-side energy storage are taken as a cooperative shared decision variable of the transmission network and the distribution network;
s4: combining the bilateral energy storage model and a shared decision variable to establish a transmission and distribution network bilateral energy storage collaborative planning model;
s5: and decomposing the transmission and distribution network of the established collaborative planning model, and then alternately and iteratively solving to obtain a transmission and distribution network double-side energy storage collaborative planning result.
Further, the power transmission network comprises a generator set, a transformer substation, a power transmission line, a centralized new energy generator and a centralized energy storage unit; the power distribution network comprises a transformer substation, a distribution network line, a distributed new energy unit, a distributed energy storage unit and a double-side energy storage unit;
The related raw data comprises transmission network raw data and distribution network raw data.
Further, the grid raw data includes: active and reactive power of a generator set and a transformer substation load, original parameters of a transmission line, access nodes and capacity of a centralized new energy generator, alternative access nodes of a centralized energy storage unit, capacity limit values and power limit values;
The original data of the power distribution network comprises: the method comprises the steps of connecting and interacting an active power limit value and a reactive power limit value of a power distribution network and a power transmission network, active power and reactive power of loads on feeder lines of the power distribution network, access nodes and capacity of a distributed new energy unit, alternative access nodes of a distributed energy storage unit, capacity limit values and power limit values, rated power, rated capacity and initial capacity of a double-sided energy storage unit which can face a power transmission network side and a power distribution network side, self-discharge rate and charge-discharge efficiency and a charge state limit value.
Further, the step S2 of constructing a double-sided energy storage model for decoupling the real-time power balance constraint of the transmission network and the distribution network includes constructing a double-sided energy storage model for decoupling the real-time power balance constraint of the transmission network and the distribution network by using the following formula:
Wherein: p T,BS is the rated power of the two-sided energy storage face to the grid side, Charging power and discharging power facing to the power transmission network side respectively,/>The variable is 0/1 of the variable which marks the charging and discharging states of the converter, and the converter facing the power transmission network side is marked in the formula (3) to be in one state of charging, discharging or not outputting; p D,BS is the rated power of the double-sided energy storage facing the power distribution network side,/>Charging power and discharging power facing the distribution network side respectively,The variables are 0/1 of the variables which mark the charge and discharge states of the battery respectively; m 1、M2 is a sufficiently large positive number; scheduling control of active power is only considered in double-side energy storage, and active power/>, flowing through main transformer of contact substation of transmission and distribution networkAnd reactive powerMeets upper and lower limit constraint formulas (7) and (8); q xline,min and Q xline,max represent a minimum allowable value and a maximum allowable value of reactive power flowing through a main transformer of a contact substation of a transmission and distribution network, respectively; p xline,min and P xline,max represent the minimum and maximum allowable values, respectively, of active power flowing through the main transformer of the tie substation of the transmission and distribution network.
Further, the charge state of the double-side energy storage in the operation process is updated as follows:
SoCminEBS≤Es,t≤SoCmaxEBS (10)
Es,1＝Es,T＝Eini (11)
Wherein: e s,t is the electric quantity stored in the double-side energy storage t period, E s,t-1 is the electric quantity stored in the double-side energy storage t-1 period, and E BS is the rated capacity of double-side energy storage; And η S are the self-discharge rate and the charge-discharge efficiency respectively, soC max、SoCmin is the maximum and minimum state of charge values respectively, and E ini is the initial capacity of double-sided energy storage; e s,1 represents the electric quantity stored in the double-sided energy storage at the beginning time of the scheduling period, and E s,T represents the electric quantity stored in the double-sided energy storage at the ending time of the scheduling period; similar to double-sided energy storage, grid centralized energy storage and distribution grid distributed energy storage also have energy storage operation charge and discharge constraints and energy storage state of charge update constraints.
Further, in the step S4, a dual-side energy storage collaborative planning model of the transmission and distribution network is established, including establishing an objective function and constraint conditions; wherein the objective function is the following formula (9):
minCTD＝CT(zT,xT,yTD,RTD)+CD(zD,xD,yTD,RTD) (9)
the constraint is the following formulas (10) - (14):
AeqT(zT,xT,yTD)＝0 (10)
HT(zT,xT,yTD)≤0 (11)
AeqD(zD,xD,yTD)＝0 (12)
HD(zD,xD,yTD)≤0 (13)
NormD(zD,xD,yTD)≤0 (14)
wherein: c T(L)、CD (L) represents an objective function, namely planning operation cost of a power transmission network and a power distribution network, and comprises annual investment cost and annual operation scheduling cost; z T、zD is an investment decision variable set of a power transmission network and a power distribution network respectively, x T、xD is a scheduling operation decision variable set of the power transmission network and the power distribution network respectively, y TD is a charge-discharge strategy of double-side energy storage, wherein, Together with the time-sharing absorption subsidy strategy R TD, the time-sharing absorption subsidy strategy R TD is used as a shared decision variable between the transmission and distribution networks; aeq T(L)、HT (L) and Aeq D(L)、HD (L) are equality constraints and inequality constraints which are required to be met by a transmission network and a distribution network respectively, and Norm D (L) is a second-order cone power flow constraint of the distribution network.
Further, the cost of the power distribution network after considering the time-sharing subsidy strategy is as follows:
wherein: c Inv,DS、CInv,BS is the annual investment costs of distributed energy storage and double-sided energy storage in the distribution network, The operation and maintenance costs of the k-th distributed energy storage device and the double-side energy storage power station in the scene s are respectively; c Subsidy is the patch of the power distribution network in the scene s, which is given by the transmission network and used for absorbing the main network waste wind and waste light;
in the cooperative planning of the transmission and distribution network, after a time-sharing absorption subsidy strategy is considered, the cooperative planning cost calculation of the transmission network part comprises unit coal consumption cost, unit transformation cost, line capacity expansion cost, electricity discarding punishment cost, the cost of removing the centralized energy storage of the coupling node, and the wind discarding and light discarding absorption subsidy of the distribution network:
minCT＝CG+CL+CCES+CAban+CSubsidy(RTD,yTD) (16)
Wherein: c Subsidy(RTD,yTD) represents that the abandoned wind and abandoned light absorption subsidy given to the power distribution network in the power transmission network is a function determined by a time-sharing absorption subsidy strategy R TD and a charge and discharge strategy y TD of double-side energy storage.
Further, in the step S5, the transmission and distribution network decomposition is performed on the established collaborative planning model, including decomposing the collaborative planning model (9) into a main transmission network planning problem and a sub-distribution network planning problem;
the main power transmission network planning problem is changed into a source network load storage optimization scheduling problem shown in a formula (17):
Wherein: the superscript "-" denotes a planning decision variable in a grid planning problem during an iteration And sharing decision variables/>Scheduling an operation decision variable x T and a time-sharing consumption subsidy strategy R TD as variables to be optimized for known parameters;
after the wind and light discarding and repairing strategy in the main problem is transmitted to the power distribution network, the power distribution network planning sub-problem is changed into:
wherein: the decision variables to be optimized of the power distribution network planning sub-problem are a planning variable z D, a scheduling operation variable x D and a shared decision variable y TD, and the subsidy strategy In this case, known parameters are used.
Further, in the step S5, the result of the collaborative planning of the energy storage of the two sides of the transmission and distribution network is obtained by alternately and iteratively solving, which comprises the following steps:
step 1): setting the maximum iteration times L, K of the inner layer and the outer layer of the distributed optimization framework and the initial iteration times l=1 and k=1, and setting the initial absorption waste wind waste light patch coefficient
Step 2): determining nodes of connection between a power distribution network and a power transmission network, firstly considering active loads and reactive loads on various feed lines of the power distribution network after the power distribution network is accessed by considering distributed new energy as actual loads of the power distribution network to the power transmission network, solving a power transmission network source network load storage planning problem by combining active load and reactive load demands of the power transmission network to obtain a source network load storage planning result z T of the power transmission network, and taking planning variables as determined values when the power transmission network main problem is solved in subsequent iteration
Step 3): obtaining a planning result of the power transmission networkThen, the centralized energy storage of the coupling nodes of the transmission and distribution network is removed
Dividing, substituting the primary problem of power transmission network planning to obtain an initial wind and light discarding curve of the nodeThe maximum new energy absorbing capacity of the node under the condition of no power distribution network response is evaluated;
step 4): the initial wind-discarding light-discarding curve and the time-sharing absorption patch strategy obtained in the step 3 are subjected to Transmitting the annual average cost/>, to a planning sub-problem of the power distribution network to obtain the annual average cost/>, of the power distribution networkDistribution network planning result z D and bilateral energy storage operation variable/>
Step 5): will beTransmitted to a main problem of a power transmission network for solving, and rechecking the planning and operation cost/>, of the power transmission networkObtaining updated abandoned wind and abandoned light curves/>
Step 6): carrying out optimality convergence judgment on the inner layer iteration result; if the total cost convergence criterion of the transmission and distribution network in the formula (19) is met, proceeding to the next step, if the total cost convergence criterion is not met, jumping back to the step 4 to start a new inner layer iteration;
Step 7): performing convergence judgment on the outer layer iteration, judging whether the new energy power rejection rate of the power transmission network and the collaborative planning cost of the power transmission network meet a convergence criterion (20), and if so, ending the problem solving; if not, the transmission network is based on the corrected light rejection curve obtained in step 5) Updating the abandoned light absorption patch coefficient according to the formula (21), returning to the step 4), solving again, resetting l=1, and enabling k=k+1;
Wherein: The method comprises the steps of (1) generating power for new energy of a power transmission network in a scene s in a t period; c T,IP、CD,IP is the annual cost of independent planning of a power transmission network and a power distribution network respectively; /(I) The patch coefficients are consumed for the abandoned wind and the abandoned light of the t period in the scene s of the kth iteration of the outer layer; /(I)After solving the power distribution network planning problem, the power transmission network re-solves the corrected abandoned wind and abandoned light power obtained by optimizing the scheduling problem according to the net load of the power distribution network,/>And (5) discarding the set of optical power for the outer layer kth iteration.
In summary, the embodiment of the invention provides a transmission and distribution network double-sided energy storage collaborative planning method considering the charge-storage coupling characteristic of a source network, which respectively constructs a transmission and distribution network double-sided energy storage model and a time-sharing light-discarding and light-absorbing patch strategy aiming at the problem of difficult energy consumption of a high proportion new energy source of the transmission and distribution network, uniformly considers the two-sided energy storage model and the time-sharing light-absorbing patch strategy into a collaborative planning model of energy storage of the transmission and distribution network, the constructed double-sided energy storage model and the time-sharing light-absorbing patch strategy can well coordinate the scheduling operation of various flexible resources in the transmission and distribution network, the distribution network can assist the transmission and distribution network to carry out wind-discarding and light-absorbing patch, the transmission and distribution network can give the power distribution network light-absorbing patch to reduce the operation cost of the distribution network, and the two parties coordinate each other, so that the collaborative result is better than the independent planning of each. The technical method provided by the embodiment of the invention has the following beneficial technical effects:
(1) The problems of less schedulable flexible resources, low transmission and distribution network cooperative efficiency and high planning cost in the current research are solved.
(2) The method realizes that the double-side energy storage of the transmission and distribution network is applied to the collaborative planning of the transmission and distribution network, and solves the problem that the energy storage capacity of the transmission network side and the distribution network side is difficult to reasonably optimize configuration and application.
Drawings
Fig. 1 is a flowchart of a transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics provided by an embodiment of the invention.
Fig. 2 is a diagram of the result of planning the layer of the IEEE-30 node transmission network coordinated with the transmission and distribution network.
Fig. 3 is a graph of distributed energy storage planning results of an IEEE-33 node power distribution network with coordinated transmission and distribution networks.
Detailed Description
The objects, technical solutions and advantages of the present invention will become more apparent by the following detailed description of the present invention with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present invention should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The use of the terms "first," "second," and the like in one or more embodiments of the present invention does not denote any order, quantity, or importance, but rather the terms "first," "second," and the like are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.
The technical scheme of the invention is described in detail below with reference to the accompanying drawings. The embodiment of the invention provides a transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics. Fig. 1 shows a flow chart of the transmission and distribution network double-side energy storage collaborative planning method, and as shown in fig. 1, the method specifically comprises the following steps:
S1: reading in relevant original data of a power system to be planned; the power system to be planned comprises a power transmission network and a power distribution network. The power transmission network comprises a generator set, a transformer substation, a power transmission line, a centralized new energy generator and a centralized energy storage unit; the power distribution network comprises a transformer substation, a distribution network line, a distributed new energy unit, a distributed energy storage unit and a double-side energy storage unit;
The related original data comprise transmission network original data and distribution network original data;
The grid raw data includes: active and reactive power of a generator set and a transformer substation load, original parameters of a transmission line, access nodes and capacity of a centralized new energy generator, alternative access nodes of a centralized energy storage unit, capacity limit values and power limit values;
The original data of the power distribution network comprises: the method comprises the steps of connecting and interacting an active power limit value and a reactive power limit value of a power distribution network and a power transmission network, active power and reactive power of loads on feeder lines of the power distribution network, access nodes and capacity of a distributed new energy unit, alternative access nodes of a distributed energy storage unit, capacity limit values and power limit values, rated power, rated capacity and initial capacity of a double-sided energy storage unit which can face a power transmission network side and a power distribution network side, self-discharge rate and charge-discharge efficiency and a charge state limit value.
S2: and constructing a double-sided energy storage model for decoupling real-time power balance constraint of the transmission network and the distribution network by utilizing the original data.
S3: and a time-sharing consumption subsidy strategy for connecting the cooperative operation between the transmission network and the distribution network is formulated, and the strategy is taken as a shared decision variable of the cooperation of the transmission network and the distribution network together with a charge-discharge strategy of double-side energy storage.
S4: and establishing a transmission and distribution network double-side energy storage collaborative planning model by combining the double-side energy storage model and a shared decision variable.
S5: and decomposing the transmission and distribution network of the established collaborative planning model, and then alternately and iteratively solving to obtain a transmission and distribution network double-side energy storage collaborative planning result.
The method comprises the steps of S2, constructing a double-sided energy storage model for decoupling real-time power balance constraint of a power transmission network and a power distribution network, wherein the double-sided energy storage power station is mainly characterized in that the double-sided energy storage power station can charge one side and discharge the other side simultaneously, and can realize decoupling of charge and discharge power to the power transmission network and the power distribution network respectively in the same set of energy storage equipment; only one set of battery management system is arranged in the double-side energy storage, electric quantity information of each battery module is mainly collected through an information bus, and each module is coordinated through a power bus to carry out charge and discharge control, so that on one hand, instructions of double-side power output are met, on the other hand, electric quantity states of each module are balanced, and overcharge or overdischarge phenomena are avoided; the inside of the double-side energy storage is provided with a plurality of sets of battery modules, so that the power of each set of battery can be independently regulated and controlled, and the discharging of part of battery packs in the inside of the large-scale energy storage and the control of part of battery packs in a charging state are realized;
Specific mathematical expressions for the planned double-sided energy storage model include:
Wherein: p T,BS is the rated power of the two-sided energy storage face to the grid side, Charging and discharging power facing the net conveying side respectively,/>The variable is 0/1 of the variable which marks the charging and discharging states of the converter, and the converter facing the power transmission network side is marked in the formula (3) to be in one state of charging, discharging or not outputting; p D,BS is the rated power of the double-sided energy storage facing the power distribution network side,/>The charging and discharging power facing the distribution network side respectively,The variables are 0/1 of the variables which mark the charge and discharge states of the battery respectively; m 1、M2 is a sufficiently large positive number; scheduling control of active power is only considered in double-side energy storage, and active power/>, flowing through main transformer of contact substation of transmission and distribution networkAnd reactive powerOnly the upper and lower limit constraint formulas (7) and (8) are required to be satisfied. Q xline,min and Q xline,max represent a minimum allowable value and a maximum allowable value of reactive power flowing through a main transformer of a contact substation of a transmission and distribution network, respectively; p xline,min and P xline,max represent the minimum and maximum allowable values, respectively, of active power flowing through the main transformer of the tie substation of the transmission and distribution network.
The step S3 is to construct a time-sharing absorption subsidy strategy, namely to design a time-sharing absorption subsidy strategy R TD, separate the originally conflicting cooperative targets of the transmission network and the distribution network, enable the transmission network to give the distribution network an auxiliary absorption and waste light subsidy, enable the energy storage on two sides to mainly play roles of peak clipping and valley filling and auxiliary absorption and waste light emission of the transmission network, and enable the power distribution network side to mainly play roles of auxiliary absorption and waste light emission of the transmission network and reduction of the operation cost of the distribution network;
The patch policy R TD and the output y TD for optimizing the double-side energy storage enable two sides of a transmission and distribution network to be connected through sharing decision variables, namely R TD and y TD, and compared with the existing transmission and distribution network collaborative method, the real-time active and reactive power balance constraint P t TG＝Pt DN of the transmission and distribution network is realized through the double-side energy storage charging and discharging policy y TD, Decoupling and serving as constraint conditions of the transmission and distribution network, and linking the cooperative operation of the transmission and distribution network through a time-sharing absorption subsidy strategy R TD.
In S4, considering the source network load storage coupling characteristic, including: the four types of flexible resources including source, network, load and storage are modeled respectively at investment and operation levels aiming at the four types of flexible resources, and finally, the model and cost function of each part of flexible resources are unified, and the whole energy storage collaborative planning model of the transmission and distribution network is considered.
In S4, a transmission and distribution network energy storage collaborative planning model considering the source network charge storage coupling characteristic is established, and the transmission and distribution network energy storage collaborative planning model specifically comprises an integral objective function (9) and constraint conditions (10) - (14):
minCTD＝CT(zT,xT,yTD,RTD)+CD(zD,xD,yTD,RTD) (9)
AeqT(zT,xT,yTD)＝0 (10)
HT(zT,xT,yTD)≤0 (11)
AeqD(zD,xD,yTD)＝0 (12)
HD(zD,xD,yTD)≤0 (13)
NormD(zD,xD,yTD)≤0 (14)
Wherein: c T(L)、CD (L) is the planning operation cost of the power transmission network and the power distribution network, namely an objective function, and comprises the annual investment cost and the annual operation scheduling cost; z T、zD is an investment decision variable set of a power transmission network and a power distribution network respectively, x T、xD is a scheduling operation decision variable set of the power transmission network and the power distribution network respectively, y TD is a charging and discharging strategy of double-side energy storage, and the method specifically comprises the following steps of Together with the time-sharing absorption subsidy strategy R TD, the time-sharing absorption subsidy strategy R TD is used as a shared decision variable between the transmission and distribution networks; aeq T(L)、HT (L) and Aeq D(L)、HD (L) are equality constraints and inequality constraints which are required to be met by a transmission network and a distribution network respectively, and Norm D (L) is a second-order cone power flow constraint of the distribution network;
The owner of two side energy storage power stations is the distribution network, and the distribution network part mainly utilizes two side energy storage power stations and inside distributed energy storage as flexible resource to assist the transmission network to consume the wind abandon light, then earns the wind abandon light that the transmission network gave and consume the subsidy with balanced energy storage device increase the operation cost promotion that brings, takes into account the cost of distribution network after the policy of time-sharing consumption subsidy:
wherein: c Inv,DS、CInv,BS is the annual investment costs of distributed energy storage and double-sided energy storage in the distribution network, The operation and maintenance costs of the k-th distributed energy storage device and the double-side energy storage power station in the scene s are respectively; c Subsidy is the patch of the power distribution network in the scene s, which is given by the transmission network and used for absorbing the main network waste wind and waste light;
in the cooperative planning of the transmission and distribution network, after a time-sharing absorption subsidy strategy is considered, the cooperative planning cost calculation of the transmission network part comprises unit coal consumption cost, unit transformation cost, line capacity expansion cost, electricity discarding punishment cost, the cost of removing the centralized energy storage of the coupling node, and the wind discarding and light discarding absorption subsidy of the distribution network:
minCT＝CG+CL+CCES+CAban+CSubsidy(RTD,yTD) (16)
Wherein: c Subsidy(RTD,yTD) represents that the abandoned wind and abandoned light absorption subsidy given to the power distribution network in the power transmission network is a function determined by a time-sharing absorption subsidy strategy R TD and a charge and discharge strategy y TD of double-side energy storage.
In S5, decomposing the transmission and distribution network of the established collaborative planning model, specifically decomposing the collaborative planning model (9) into a main transmission network planning problem and a sub-distribution network planning problem;
the main power transmission network planning problem is changed into a source network load storage optimization scheduling problem shown in a formula (17):
Wherein: the superscript "-" denotes a planning decision variable in a grid planning problem during an iteration And sharing decision variables/>Scheduling an operation decision variable x T and a time-sharing consumption subsidy strategy R TD as variables to be optimized for known parameters;
after the wind and light discarding and repairing strategy in the main problem is transmitted to the power distribution network, the power distribution network planning sub-problem is changed into:
wherein: the decision variables to be optimized of the power distribution network planning sub-problem are a planning variable z D, a scheduling operation variable x D and a shared decision variable y TD, and the subsidy strategy In this case, known parameters are used.
The method comprises the following steps of (S5) alternately and iteratively solving to obtain the power, capacity and time-sharing absorption patch strategy result of the transmission and distribution network double-side energy storage collaborative planning, wherein the method specifically comprises the following steps:
step 1): setting the maximum iteration times L, K of the inner layer and the outer layer of the distributed optimization framework and the initial iteration times l=1 and k=1, and setting the initial absorption waste wind waste light patch coefficient
Step 2): determining nodes of connection between a power distribution network and a power transmission network, firstly considering the net load of an active power distribution network after the access of a distributed new energy source is considered as the actual load of the power distribution network to the power transmission network, solving a power transmission network source load storage planning problem to obtain a power transmission network source load storage planning result z T of the power transmission network, and taking a planning variable as a determined value when the main problem of the power transmission network is solved in a subsequent iteration mode
Step 3): obtaining a planning result of the power transmission networkAnd then, removing centralized energy storage of the coupling nodes of the transmission and distribution network, substituting the centralized energy storage into a main planning problem of the transmission and distribution network to obtain an initial wind and light discarding curve/>, of the nodeThe maximum new energy absorbing capacity of the node under the condition of no power distribution network response is evaluated;
step 4): the initial wind-discarding light-discarding curve and the time-sharing absorption patch strategy obtained in the step 3 are subjected to Transmitting the annual average cost/>, to a planning sub-problem of the power distribution network to obtain the annual average cost/>, of the power distribution networkDouble-sided energy storage operating variable/>
Step 5): will beTransmitted to a main problem of a power transmission network for solving, and rechecking the planning and operation cost/>, of the power transmission networkObtaining updated abandoned wind and abandoned light curves/>
Step 6): carrying out optimality convergence judgment on the inner layer iteration result; if the total cost convergence criterion of the transmission and distribution network in the formula (19) is met, proceeding to the next step, if the total cost convergence criterion is not met, jumping back to the step 4 to start a new inner layer iteration;
step 7): performing convergence judgment on the outer layer iteration, judging whether the new energy power rejection rate of the power transmission network and the collaborative planning cost of the power transmission network meet a convergence criterion (20), and ending the problem solving if the new energy power rejection rate and the collaborative planning cost of the power transmission network meet the convergence criterion; if not, the transmission network is based on the corrected light rejection curve obtained in step 5 Updating the abandoned light absorption patch coefficient according to the formula (21), returning to the step (4) to solve again, resetting l=1, and enabling k=k+1;
Wherein: The method comprises the steps of (1) generating power for new energy of a power transmission network in a scene s in a t period; c T,IP、CD,IP is the annual cost of independent planning of a power transmission network and a power distribution network respectively; /(I) The patch coefficients are consumed for the abandoned wind and the abandoned light of the t period in the scene s of the kth iteration of the outer layer; /(I)After solving the power distribution network planning problem, the power transmission network re-solves the corrected abandoned wind and abandoned light power obtained by optimizing the scheduling problem according to the net load of the power distribution network,/>The method comprises the steps of (1) discarding a set of optical power for the outer layer kth iteration; the purpose of the formula (21) is to give a higher subsidy to attract the power distribution network to absorb during the high-wind-discarding period, gradually tighten the coefficient lifting amplitude in the later iteration period and find the optimal solution of the collaborative planning.
The technical scheme of the invention is described below by taking an IEEE-30 node transmission network model as a transmission network and an IEEE-33 node distribution network model as a distribution network. Fig. 2 shows a layer planning result diagram of the IEEE-30 node transmission network coordinated with the transmission and distribution network, and fig. 3 shows a distributed energy storage planning result diagram of the IEEE-33 node distribution network coordinated with the transmission and distribution network. As shown in fig. 2, where the numbers represent node numbers of node bus bars in the power transmission network, the dark G represents the unit transformed in the collaborative planning, the light G represents the original generator set in the power transmission network, DR represents the load of the power transmission network, PV represents the new energy photovoltaic generator set, DN represents the power distribution network connected to the power transmission network, ESS represents the newly installed energy storage device after the collaborative planning, the dark black line represents the power transmission line, and the light thick line represents the line expanded after the collaborative planning. Fig. 2 shows the expansion of the transmission network line and the unit planning result, and as can be seen from fig. 2, after collaborative planning, the generators at the nodes 1,2 and 22 are subjected to unit transformation and upgrading. In addition, the capacity of 10 lines in total is expanded and upgraded, and the new energy stations except the node 11 are provided with energy storage devices, so that the total energy storage capacity is 71.3MW/282.9MWh. Fig. 3 shows the result of distributed energy storage planning in a power distribution network under collaborative planning. As can be seen from fig. 3, after collaborative planning, a distribution network creates a new distributed energy storage at nodes 12, 19, 21, 28 and 33, and the total energy storage is 22MW/110MWh. In addition, 6, 13, 12, 24 nodes in the power distribution network are connected with distributed wind power, and 18 and 33 nodes are connected with distributed photovoltaic. The planning result shows that the distributed energy storage installation nodes are close to the balance nodes or near the distributed power supply, so that the auxiliary power distribution network can better consume new energy.
With reference to fig. 1 to fig. 3, the transmission and distribution network double-side energy storage collaborative planning method considering the source network charge storage coupling characteristic provided by the embodiment of the invention includes the following steps:
step S1, reading in relevant original data of each part of source network charge storage of a power system to be planned.
The reference voltages of the transmission network and the distribution network are 135kV and 12.66kV respectively, and the maximum load is 405MW. The power transmission network is respectively connected with a 75MW photovoltaic power station at nodes 11, 17 and 25, the node 14 is connected with a 100M photovoltaic power station, the new energy permeability is about 41%, a 50MW/1000MWh pumped storage power station is configured at node 4, the deployment of DR is changed, the access nodes are 9, 17 and 25, and the capacity is 10MW; the node to be installed for storing energy is the node where the new energy station is located, and the candidate capacity expansion lines are 41 lines in total of the whole network. The candidate reforming unit is still 6 generators in the whole network. Each centralized energy storage power station is limited to a maximum of 30MW/120MWh. The total load of the active power distribution network is 22.29MW, 14 nodes of the power transmission network are connected, 4 distributed wind power stations are arranged in the power distribution network, 2 distributed photovoltaic power stations are arranged in the power distribution network, the new energy power generation amount accounts for 39%, and the distributed energy storage candidate positions are nodes 2 to 33. The unit power rejection penalty is 3 yuan/kWh.
Step S2, a double-side energy storage model for decoupling real-time power balance constraint of a transmission network and a distribution network is constructed and used as power and quantity balance equipment between the transmission network and the distribution network. Mathematical expressions of a double sided energy storage model as described in the specification.
And step S3, formulating a time-sharing consumption subsidy strategy for connecting the cooperative operation between the transmission and the distribution network, wherein the strategy and a charge and discharge strategy of double-side energy storage are taken as a cooperative shared decision variable of the transmission and the distribution network. The variables of the subsidy policy R TD are designed as described in the specification and need to be solved together according to step S5.
And S4, establishing a transmission and distribution network energy storage collaborative planning model by considering the source network charge storage coupling characteristic. A mathematical expression of a detailed planning model as described in the specification.
And S5, decomposing the transmission and distribution network of the established collaborative planning model, and then alternately and iteratively solving to obtain the result of power, capacity and time-sharing absorption patch strategy of the transmission and distribution network double-side energy storage collaborative planning.
The invention solves the cooperative planning model and alternate iteration of the transmission and distribution network by utilizing the constructed double-side energy storage model and the time-sharing absorption patch strategy, and the result shows that the total cost of the cooperative system of the transmission and distribution network is 7.46 multiplied by 10 8 yuan, which is 3.34 percent lower than the total cost of the independent planning, wherein the electricity discarding penalty cost is 41.79 percent lower.
As shown in table 1, the annual operating cost of the distribution network under collaborative planning is reduced by 14.07% compared with independent planning. In collaborative planning, the distribution network is configured with more energy storage devices to assist the transmission network in dissipating more waste wind and light. Meanwhile, the distributed power supply in the power distribution network and the centralized photovoltaic power station of the power transmission network are overlapped in the power generation peak period, and in the period, the absorption patch coefficient given by the power transmission network is higher than the electric discarding penalty, so that the power distribution network can preferentially assist the power transmission network to absorb the wind discarding and the light discarding. The total cost is reduced due to the existence of the wind-discarding light-discarding subsidy, although the electricity-discarding penalty of the distribution network is increased. At the moment, the power rejection rate of the distributed new energy in the power distribution network is 3.83%.
As shown in table 2, the annual average cost of the grid in collaborative planning is reduced by 2.03% compared with independent planning, and the cost is mainly reduced in terms of electricity discarding penalty and energy storage investment operation maintenance cost. After the centralized energy storage is replaced by the double-side energy storage, the centralized energy storage investment and the operation cost of the power transmission network are reduced by 45.68%, secondly, the power transmission network has a power transmission penalty reduced by 51.15% due to the fact that the power transmission network is assisted by the power distribution network to consume the waste wind and waste light, and the total cost is still reduced and the total waste wind and waste light rate of the power transmission network is only 1.48% although the power distribution network needs to be given about 3.28X10 7 yuan for one year to consume the patch.
Table 1 distribution network planning result unit: millions of yuan
Table 2 grid planning result units: millions of yuan
The transmission and distribution network double-side energy storage model and the time-sharing absorption patch strategy constructed by the invention can well coordinate the scheduling operation of various resources in the transmission and distribution network, the power distribution network can assist the transmission network to carry out the wind-discarding and light-discarding absorption, the transmission network can give the wind-discarding and light-discarding absorption patch of the power distribution network to reduce the operation cost of the power distribution network, the two parties coordinate with each other, the cooperative result is better than the independent planning of each party, and the alternate iteration optimization framework can obtain the result in the 3 rd round of iteration.
It should be understood that the above discussion of any of the embodiments is exemplary only and is not intended to suggest that the scope of the invention (including the claims) is limited to these examples; combinations of features of the above embodiments or in different embodiments are also possible within the spirit of the invention, steps may be implemented in any order and there are many other variations of the different aspects of one or more embodiments of the invention described above which are not provided in detail for the sake of brevity. The above detailed description of the present invention is merely illustrative or explanatory of the principles of the invention and is not necessarily intended to limit the invention. Accordingly, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present invention should be included in the scope of the present invention. Furthermore, the appended claims are intended to cover all such changes and modifications that fall within the scope and boundary of the appended claims, or equivalents of such scope and boundary.
Claims (5)
1. A transmission and distribution network double-side energy storage collaborative planning method considering source network charge storage coupling characteristics is characterized by comprising the following steps:
s1: reading in relevant original data of a power system to be planned; the power system to be planned comprises a power transmission network and a power distribution network;
S2: constructing a double-sided energy storage model for decoupling real-time power balance constraint of a power transmission network and a power distribution network by utilizing the original data; the method comprises the steps of constructing a double-sided energy storage model for decoupling real-time power balance constraint of a transmission network and a distribution network by using the following formula:
Wherein: p T,BS is the rated power of the two-sided energy storage face to the grid side, Charging power and discharging power facing to the power transmission network side respectively,/>The variable is 0/1 of the variable which marks the charging and discharging states of the converter, and the converter facing the power transmission network side is marked in the formula (3) to be in one state of charging, discharging or not outputting; p D,BS is the rated power of the double-sided energy storage facing the power distribution network side,/>Charging power and discharging power facing the distribution network side respectively,The variables are 0/1 of the variables which mark the charge and discharge states of the battery respectively; m 1、M2 is a sufficiently large positive number; scheduling control of active power is only considered in double-side energy storage, and active power/>, flowing through main transformer of contact substation of transmission and distribution networkAnd reactive powerMeets upper and lower limit constraint formulas (7) and (8); q xline,min and Q xline,max represent a minimum allowable value and a maximum allowable value of reactive power flowing through a main transformer of a contact substation of a transmission and distribution network, respectively; p xline,min and P xline,max respectively represent a minimum allowable value and a maximum allowable value of active power of the main transformer of the contact substation flowing through the transmission and distribution network;
s3: a time-sharing consumption subsidy strategy for connecting the cooperative operation between a transmission network and a distribution network is formulated, and the strategy and a charge-discharge strategy of double-side energy storage are taken as a cooperative shared decision variable of the transmission network and the distribution network;
S4: combining the bilateral energy storage model and a shared decision variable to establish a transmission and distribution network bilateral energy storage collaborative planning model; the method comprises the steps of establishing an objective function and constraint conditions; wherein the objective function is the following formula (9):
minCTD＝CT(zT,xT,yTD,RTD)+CD(zD,xD,yTD,RTD) (9)
the constraint is the following formulas (10) - (14):
AeqT(zT,xT,yTD)＝0 (10)
HT(zT,xT,yTD)≤0 (11)
AeqD(zD,xD,yTD)＝0 (12)
HD(zD,xD,yTD)≤0 (13)
NormD(zD,xD,yTD)≤0 (14)
Wherein: c T(…)、CD (…) represents an objective function, which is the planned running cost of the transmission network and the distribution network respectively, including the annual investment cost and the annual running scheduling cost; z T、zD is an investment decision variable set of a power transmission network and a power distribution network respectively, x T、xD is a scheduling operation decision variable set of the power transmission network and the power distribution network respectively, y TD is a charge-discharge strategy of double-side energy storage, wherein, Together with the time-sharing absorption subsidy strategy R TD, the time-sharing absorption subsidy strategy R TD is used as a shared decision variable between the transmission and distribution networks; aeq T(…)、HT (…) and Aeq D(…)、HD (…) are equality constraints and inequality constraints which are required to be met by a transmission network and a distribution network respectively, and Norm D (…) is a second-order cone power flow constraint of the distribution network;
S5: decomposing the transmission and distribution network of the established collaborative planning model, and then alternately and iteratively solving to obtain a transmission and distribution network double-side energy storage collaborative planning result; the method comprises the steps that transmission and distribution network decomposition is carried out on the established collaborative planning model, wherein the collaborative planning model (9) is decomposed into a main transmission network planning problem and a sub-distribution network planning problem;
the main power transmission network planning problem is changed into a source network load storage optimization scheduling problem shown in a formula (17):
Wherein: the superscript "-" denotes a planning decision variable in a grid planning problem during an iteration Sharing decision variablesScheduling an operation decision variable x T and a time-sharing consumption subsidy strategy R TD as variables to be optimized for known parameters; The method is characterized in that the abandoned wind and abandoned light absorption subsidy given to the power distribution network in the power transmission network is a function determined by a time-sharing absorption subsidy strategy R TD and a charge-discharge strategy y TD of double-side energy storage;
after the wind and light discarding and repairing strategy in the main problem is transmitted to the power distribution network, the power distribution network planning sub-problem is changed into:
wherein: the decision variables to be optimized of the power distribution network planning sub-problem are a planning variable z D, a scheduling operation variable x D and a shared decision variable y TD, and the subsidy strategy In this case, as a known parameter;
the alternate iterative solution comprises the steps of:
step 1): setting the maximum iteration times L, K of the inner layer and the outer layer of the distributed optimization framework and the initial iteration times l=1 and k=1, and setting the initial absorption waste wind waste light patch coefficient
Step 2): determining nodes of connection between a power distribution network and a power transmission network, firstly considering active loads and reactive loads on various feed lines of the power distribution network after the power distribution network is accessed by considering distributed new energy as actual loads of the power distribution network to the power transmission network, solving a power transmission network source network load storage planning problem by combining active load and reactive load demands of the power transmission network to obtain a source network load storage planning result z T of the power transmission network, and taking planning variables as determined values when the power transmission network main problem is solved in subsequent iteration
Step 3): obtaining a planning result of the power transmission networkAnd then, removing centralized energy storage of the coupling nodes of the transmission and distribution network, substituting the centralized energy storage into a main planning problem of the transmission and distribution network to obtain an initial wind and light discarding curve/>, of the nodeThe maximum new energy absorbing capacity of the node under the condition of no power distribution network response is evaluated;
step 4): the initial wind-discarding light-discarding curve and the time-sharing absorption patch strategy obtained in the step 3 are subjected to Transmitting the annual average cost/>, to a planning sub-problem of the power distribution network to obtain the annual average cost/>, of the power distribution networkDistribution network planning result z D and bilateral energy storage operation variable/>
Step 5): will beTransmitted to the main problem of the power transmission network for solving, and rechecking the planning and operation cost of the power transmission networkObtaining updated abandoned wind and abandoned light curves/>
Step 6): carrying out optimality convergence judgment on the inner layer iteration result; if the total cost convergence criterion of the transmission and distribution network in the formula (19) is met, proceeding to the next step, if the total cost convergence criterion is not met, jumping back to the step 4 to start a new inner layer iteration;
Step 7): performing convergence judgment on the outer layer iteration, judging whether the new energy power rejection rate of the power transmission network and the collaborative planning cost of the power transmission network meet a convergence criterion (20), and if so, ending the problem solving; if not, the transmission network is based on the corrected light rejection curve obtained in step 5) Updating the abandoned light absorption patch coefficient according to the formula (21), returning to the step 4), solving again, resetting l=1, and enabling k=k+1;
Wherein: The method comprises the steps of (1) generating power for new energy of a power transmission network in a scene s in a t period; c T,IP、CD,IP is the annual cost of independent planning of a power transmission network and a power distribution network respectively; /(I) The patch coefficients are consumed for the abandoned wind and the abandoned light of the t period in the scene s of the kth iteration of the outer layer; /(I)After solving the power distribution network planning problem, the power transmission network re-solves the corrected abandoned wind and abandoned light power obtained by optimizing the scheduling problem according to the net load of the power distribution network,/>And (5) discarding the set of optical power for the outer layer kth iteration.
2. The method of claim 1, wherein the power grid comprises a generator set, a substation, a transmission line, a centralized new energy generator, and a centralized energy storage unit; the power distribution network comprises a transformer substation, a distribution network line, a distributed new energy unit, a distributed energy storage unit and a double-side energy storage unit;
The related raw data comprises transmission network raw data and distribution network raw data.
3. The method of claim 2, wherein the grid raw data comprises: active and reactive power of a generator set and a transformer substation load, original parameters of a transmission line, access nodes and capacity of a centralized new energy generator, alternative access nodes of a centralized energy storage unit, capacity limit values and power limit values;
The original data of the power distribution network comprises: the method comprises the steps of connecting and interacting an active power limit value and a reactive power limit value of a power distribution network and a power transmission network, active power and reactive power of loads on feeder lines of the power distribution network, access nodes and capacity of a distributed new energy unit, alternative access nodes of a distributed energy storage unit, capacity limit values and power limit values, rated power, rated capacity and initial capacity of a double-sided energy storage unit which can face a power transmission network side and a power distribution network side, self-discharge rate and charge-discharge efficiency and a charge state limit value.
4. A method according to claim 3, wherein the state of charge of the double sided energy storage during operation is updated as:
SoCminEBS≤Es,t≤SoCmaxEBS (10)
Es,1＝Es,T＝Eini (11)
Wherein: e s,t is the electric quantity stored in the double-side energy storage t period, E s,t-1 is the electric quantity stored in the double-side energy storage t-1 period, and E BS is the rated capacity of double-side energy storage; And η S are the self-discharge rate and the charge-discharge efficiency respectively, soC max、SoCmin is the maximum and minimum state of charge values respectively, and E ini is the initial capacity of double-sided energy storage; e s,1 represents the electric quantity stored in the double-sided energy storage at the beginning time of the scheduling period, and E s,T represents the electric quantity stored in the double-sided energy storage at the ending time of the scheduling period; similar to double-sided energy storage, grid centralized energy storage and distribution grid distributed energy storage also have energy storage operation charge and discharge constraints and energy storage state of charge update constraints.
5. The method of claim 4, wherein the cost of the distribution network after considering the time-sharing subsidy strategy is:
wherein: c Inv,DS、CInv,BS is the annual investment costs of distributed energy storage and double-sided energy storage in the distribution network, The operation and maintenance costs of the k-th distributed energy storage device and the double-side energy storage power station in the scene s are respectively; c Subsidy is the patch of the power distribution network in the scene s, which is given by the transmission network and used for absorbing the main network waste wind and waste light;
In the cooperative planning of the transmission and distribution network, after the time-sharing consumption subsidy strategy is considered, the cooperative planning cost calculation of the transmission network part comprises the unit coal consumption cost, the unit transformation cost, the line capacity expansion cost, the electricity discarding punishment cost, the centralized energy storage cost for removing the coupling node, and
Giving wind and light discarding and absorbing patch to the power distribution network:
minCT＝CG+CL+CCES+CAban+CSubsidy(RTD,yTD) (16)
Wherein: c Subsidy(RTD,yTD) represents that the abandoned wind and abandoned light absorption subsidy given to the power distribution network in the power transmission network is a function determined by a time-sharing absorption subsidy strategy R TD and a charge and discharge strategy y TD of double-side energy storage.
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