CN113988463A - Multi-station integrated distribution network transformer substation planning method - Google Patents
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Abstract
The invention provides a multi-station integrated distribution network transformer substation planning method, which comprises the following steps: constructing a distribution network transformer substation system integrating a charging pile, a photovoltaic panel and energy storage equipment; according to the service life and the annual income of the distribution network transformer substation, the construction cost of the charging pile, the photovoltaic panel and the energy storage equipment is combined, a distribution network transformer substation planning model is constructed, and the constraint conditions of the distribution network transformer substation planning model are determined; on the basis of a particle swarm algorithm, the planning model of the distribution network transformer substation is solved on the premise of meeting constraint conditions to obtain an optimal scheme of transformer substation planning, and the number of charging piles and energy storage equipment in the distribution network transformer substation and the installation area of a photovoltaic panel are set according to the optimal scheme. The invention provides a planning scheme for a transformer substation planning method, which comprehensively considers the economy and the space adaptability in the transformer substation, and can effectively realize the planning of the provided multi-station integrated distribution network transformer substation, thereby effectively promoting the multi-station integration and the full utilization of the space resources of the transformer substation.
Description
Technical Field
The invention belongs to the field of power system planning, and particularly relates to a multi-station integrated distribution network transformer substation planning method.
Background
The multi-station integration is to construct various distributed energy sources and load units by utilizing the space in the station of the distribution network transformer substation. The multi-station fusion construction content covers an intelligent substation, a plurality of elements such as a charging pile for an electric automobile, an energy storage device and a distributed energy station, the related content and the specialty are complex, but the multi-station fusion is not only to simply construct the elements in a distribution network substation, the overall benefit of the distribution network substation is improved, the actual situation of the distribution network substation and the matching situation between different devices need to be comprehensively considered, the current research on the multi-station fusion is still in a starting stage, and a planning method capable of solving the multi-station fusion problem of the distribution network substation is needed urgently.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a multi-station integrated distribution network transformer substation planning method, which comprises the following steps:
constructing a distribution network transformer substation system integrating a charging pile, a photovoltaic panel and energy storage equipment;
according to the service life and the annual income of the distribution network transformer substation, the construction cost of the charging pile, the photovoltaic panel and the energy storage equipment is combined, a distribution network transformer substation planning model is constructed, and the constraint conditions of the distribution network transformer substation planning model are determined;
on the basis of a particle swarm algorithm, the planning model of the distribution network transformer substation is solved on the premise of meeting constraint conditions to obtain an optimal scheme of transformer substation planning, and the number of charging piles and energy storage equipment in the distribution network transformer substation and the installation area of a photovoltaic panel are set according to the optimal scheme.
Optionally, according to the service life and the annual income of the distribution network substation, the construction cost of the charging pile, the photovoltaic panel and the energy storage device is combined, and a distribution network substation planning model is constructed, including:
obtaining the service life Y and the discount rate r of the distribution network transformer substation, and calculating the equal-year-value coefficient of the distribution network transformer substation as phi:
with the maximum annual net income of the distribution network transformer substation as a target, establishing a distribution network transformer substation planning model as follows:
wherein F represents the annual net income of the distribution network transformer substation, I is the annual income of the distribution network transformer substation, CtotalFor the total construction cost of the distribution network transformer substation, D is the working days of the distribution network transformer substation, T is the total working time of the distribution network transformer substation every day, T represents the sampling time, delta T is the interval of the sampling time, P0,tThe power of the distribution network transformer substation for purchasing electricity from the power grid at the moment t, U is the unit price of the distribution network transformer substation for purchasing electricity from the power grid, n1E is the number of charging piles in the distribution network transformer substation, and e is the service unit price of the charging piles, PEV,tFor charging the output power of the pile at time t, tEVAverage operating time for charging piles, CEVConstruction costs for a single charging pile, CPVIs the photovoltaic panel construction cost per unit area, sPV,1For the construction area, s, of the photovoltaic panel on the roof of the park of the distribution network substationPV,2For the construction area, P, of the photovoltaic panel on the open ground of the garden of the distribution network substationESS,maxMaximum charge and discharge power of a single energy storage device, CESS,pCost per unit power of a single energy storage device, GmaxFor the installation capacity of a single energy storage device, CGCost per unit capacity, n, of a single energy storage device2For the number of energy storage boxes in the distribution network substation, CCS,1To communicateConstruction cost of base station on roof, CCS,2For the construction costs of the communication base stations on open ground, BCSAs a valid variable, BCSIs 1 represents effective, BCSA value of 0 indicates no effect.
Optionally, the constraint condition of the distribution network substation planning model includes at least one of a construction area constraint, a charging station output constraint and an electric quantity balance constraint.
Optionally, the construction area constraint is:
wherein s ispv,1For photovoltaic panel area, s, installed on the garden roof of a distribution network substationpv,2In order to fit the photovoltaic panel area of the garden open space of the distribution network substation,
is the unit floor space of the energy storage device,
for the unit area of the charging pile, n1For the number of energy storage devices in the distribution network substation, n2For the number of charging piles in the distribution network substation, S1Is the total area of the roof of the park, S2Is the total area of the open space of the park, S3For the out-of-station area, s, of the distribution network substationCS,1For the floor area of the communication base station on the roof, sCS,2Is the floor area of the communication base station on the air ground.
Optionally, the charging station output constraint is:
0≤PEV,t≤PEV,max；
wherein, PEV,tFor charging the output power of the pile at time t, PEV,maxThe maximum rated output power of the charging pile.
Optionally, the power balance constraint is:
P0,t+Pdch,t+PPV,t＝PEV,t+Pch,t；
wherein, P0,tPower, P, for distribution network substations purchasing electricity from the griddch,tFor discharge power of a single energy storage device at time t, PPV,tThe output of the photovoltaic panel at time t, PEV,tFor charging the output power of the pile at time t, Pch,tCharging power for a single energy storage device at time t.
Optionally, the solving is performed on the distribution network substation planning model on the premise that constraint conditions are met based on the particle swarm algorithm, so as to obtain an optimal scheme for substation planning, where the optimal scheme includes:
the method comprises the following steps: initializing the iteration times of the particle swarm algorithm, the population size speed of the particles and positions, wherein the positions are the number of charging piles of the distribution network transformer substation, the number of energy storage devices and the installation area of a photovoltaic panel on a garden roof and an open ground of the distribution network transformer substation;
step two: calculating the fitness corresponding to the current position of the particle according to the distribution network transformer substation planning model, taking the position of the particle with the minimum fitness in the previous k times of iterative calculation as an individual extreme value of the particle, and taking the position of all the particles with the minimum fitness in the previous k times of iterative calculation as a global extreme value;
step three: updating the speed and the position of the particles in the (k +1) th iterative computation based on the individual extreme value and the global extreme value;
step four: and repeating the second step to the third step until a preset iteration ending condition is met, and taking the global extreme value in the last iteration calculation as an optimal scheme.
Optionally, the third step includes:
the velocity of the particle is updated as:
v(k+1)＝ωv(k)+c1r1(pbest(k)-x(k))+c2r2(gbest(k)-x(k))；
the position of the particle is updated as:
x(k+1)＝x(k)+v(k+1)；
wherein v (k +1) is the velocity of the particle at the k +1 th iteration, v (k) is the velocity of the particle at the k-th iteration, ωFor a predetermined inertia factor, c1、c2Are preset acceleration coefficients, r, of a particle swarm algorithm1、r2Pbest (k) is the individual extreme value of the particle in the previous k iterations, gbest (k) is the global extreme value of the particle in the previous k iterations, x (k +1) is the position of the particle at the k +1 th iteration, and x (k) is the position of the particle at the k-th iteration.
The technical scheme provided by the invention has the beneficial effects that:
the method comprises the steps of establishing a transformer substation planning model and constraint conditions thereof by taking the maximum annual income of the transformer substation as an objective function; the established transformer substation planning model is solved by adopting an improved particle swarm algorithm to obtain an optimal scheme for transformer substation planning, a planning scheme comprehensively considering economy and in-station space adaptability is provided for a transformer substation planning method, and the proposed multi-station fusion distribution network transformer substation can be effectively planned, so that the full utilization of multi-station fusion and transformer substation space resources is effectively promoted, and a green, low-carbon, intelligent, high-efficiency and sustainable-development multi-station fusion distribution network transformer substation is more efficiently constructed.
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In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a multi-station-integrated distribution network and substation planning method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the distribution of available space of distribution network substations;
FIG. 3 is a flow chart of solving particle swarm optimization.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the internal logic of the processes, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
It should be understood that in the present application, "comprising" and "having" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that, in the present invention, "a plurality" means two or more. "and/or" is merely an association describing an associated object, meaning that three relationships may exist, for example, and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "comprises A, B and C" and "comprises A, B, C" means that all three of A, B, C comprise, "comprises A, B or C" means that one of A, B, C comprises, "comprises A, B and/or C" means that any 1 or any 2 or 3 of A, B, C comprises.
It should be understood that in the present invention, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, and B can be determined from a. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information. And the matching of A and B means that the similarity of A and B is greater than or equal to a preset threshold value.
As used herein, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Example one
As shown in fig. 1, this embodiment provides a multi-station integrated distribution network and substation planning method, including:
s1: constructing a distribution network transformer substation system integrating a charging pile, a photovoltaic panel and energy storage equipment;
s2: according to the service life and the annual income of the distribution network transformer substation, the construction cost of the charging pile, the photovoltaic panel and the energy storage equipment is combined, a distribution network transformer substation planning model is constructed, and the constraint conditions of the distribution network transformer substation planning model are determined;
s3: on the basis of a particle swarm algorithm, the planning model of the distribution network transformer substation is solved on the premise of meeting constraint conditions to obtain an optimal scheme of transformer substation planning, and the number of charging piles and energy storage equipment in the distribution network transformer substation and the installation area of a photovoltaic panel are set according to the optimal scheme.
The multi-station integration is to construct various distributed energy sources and load units by utilizing the space in a substation or a substation area of a transformer substation. The multi-station fusion construction content covers various elements such as an intelligent substation, an electric vehicle charging and converting station, an energy storage power station and a distributed energy source station, the related content and the professional are complex, and the actual condition of a distribution network substation and the matching condition between different devices need to be comprehensively considered. Therefore, for the multi-station integration situation, a planning model relating to the charging pile, the photovoltaic panel and the energy storage device distribution network substation is constructed, and a particle swarm algorithm is adopted to solve to obtain an optimal planning scheme.
Firstly, constructing a distribution network transformer substation planning model, which comprises the following steps:
obtaining the service life Y and the discount rate r of the distribution network transformer substation, and calculating the equal-year-value coefficient of the distribution network transformer substation as phi:
the maximum annual net income of distribution network transformer substation is used as the target in this embodiment, and the construction cost and the daily electricity purchase cost of all kinds of equipment are subtracted to the annual income of distribution network transformer substation promptly, simultaneously, and all kinds of construction costs and self service life of considering distribution network transformer substation have certain relevance, consequently introduce the influence of service life to the construction cost through the above-mentioned annual value coefficient that obtains of calculating in distribution network transformer substation planning model, specifically do:
wherein F represents the annual net income of the distribution network transformer substation, I is the annual income of the distribution network transformer substation, CtotalFor the total construction cost of the distribution network transformer substation, D is the working days of the distribution network transformer substation, T is the total working time of the distribution network transformer substation every day, T represents the sampling time, delta T is the interval of the sampling time, P0,tThe power of the distribution network transformer substation for purchasing electricity from the power grid at the moment t, U is the unit price of the distribution network transformer substation for purchasing electricity from the power grid, n1E is the number of charging piles in the distribution network transformer substation, and e is the service unit price of the charging piles, PEV,tFor charging the output power of the pile at time t, tEVAverage operating time for charging piles, CEVConstruction costs for a single charging pile, CPVIs the photovoltaic panel construction cost per unit area, sPV,1For the construction area, s, of the photovoltaic panel on the roof of the park of the distribution network substationPV,2Distribution network transformer substation for photovoltaic panelConstruction area, P, on open land of parkESS,maxMaximum charge and discharge power of a single energy storage device, CESS,pCost per unit power of a single energy storage device, GmaxFor the installation capacity of a single energy storage device, CGCost per unit capacity, n, of a single energy storage device2For the number of energy storage boxes in the distribution network substation, CCS,1Construction costs of communication base stations on roofs, CCS,2For the construction costs of the communication base stations on open ground, BCSAs an effective variable for indicating the installation mode of the communication base station, BCSIs 1, i.e. the communication base station is installed on the roof, BCSA value of 0 indicates no effect, i.e., the communication base station is installed on the air.
In this embodiment, in the calculation formula of the annual income I of the distribution network substation, the coefficient 0.6 is a rated output power to average power measurement coefficient, and the value D is 350.
In consideration of the space condition of the distribution network substation, in the embodiment, as shown in fig. 2, the energy storage device is installed in the vacant space S of the garden in the distribution network substation2The area of (2), a part of the photovoltaic panels is installed on the roof S of the garden in the distribution network substation1The other part of the area is arranged in a garden vacant space S in a distribution network substation station2The charging pile is installed outside the distribution network substation S3The region of (2) is in order to provide charging service outward, has set up the construction area restraint for distribution network transformer substation planning model based on this, include:
wherein s ispv,1For photovoltaic panel area, s, installed on the garden roof of a distribution network substationpv,2In order to fit the photovoltaic panel area of the garden open space of the distribution network substation,
is the unit floor space of the energy storage device,
for the unit area of the charging pile, n1For the number of energy storage devices in the distribution network substation, n2For the number of charging piles in the distribution network substation, S1Is the total area of the roof of the park, S2Is the total area of the open space of the park, S3For the out-of-station area, s, of the distribution network substationCS,1For the floor area of the communication base station on the roof, sCS,2Is the floor area of the communication base station on the air ground.
Simultaneously, the distribution characteristics of filling electric pile, energy storage equipment and photovoltaic board self are considered, distribution network transformer substation planning model still includes energy storage charge and discharge restraint, charging station restraint and the balanced restraint of electric quantity of exerting oneself, and wherein, energy storage charge and discharge restraint is:
where t is the sampling time, Pch,tFor charging power of individual energy storage devices at time t, Pdch,tFor discharge power of a single energy storage device at time t, PESS,maxAlpha is the depth of discharge coefficient, G, for the maximum power of the energy storage devicetCapacity of a single energy storage device at time t, Gt＝Gt-1+(ηPch,t-Pdch,tEta) at, eta is the operating efficiency of the energy storage device, at is the interval of the sampling instants, Gt-1Capacity of a single energy storage device at time t-1, GmaxThe maximum construction capacity of the energy storage device.
The output constraint of the charging station is as follows:
0≤PEV,t≤PEV,max；
wherein, PEV,tFor charging the output power of the pile at time t, PEV,maxThe maximum rated output power of the charging pile.
The electric quantity balance constraint is as follows:
P0,t+Pdch,t+PPV,t＝PEV,t+Pch,t；
wherein, P0,tSubstation slave for distribution networkPower of the electricity purchasing from the grid, Pdch,tFor discharge power of a single energy storage device at time t, PPV,tThe output of the photovoltaic panel at time t, PEV,tFor charging the output power of the pile at time t, Pch,tCharging power for a single energy storage device at time t.
In the embodiment, the energy storage constraint indirectly constrains the electric quantity balance constraint, and the distribution network transformer substation can meet the performance bearing range of energy storage operation together with the electric quantity balance constraint. Therefore, energy storage constraint can indirectly realize P in distribution network transformer substation planning modelEV,tOf (3) is performed. Through energy storage charging and discharging constraints, charging station output constraints and electric quantity balance constraints, the distribution network transformer substation planning method provided by the embodiment can synthesize economic factors and operation performance factors to obtain an optimal planning scheme.
In this embodiment, the constraint conditions of the distribution network substation planning model include at least one of a construction area constraint, an energy storage charging and discharging constraint, a charging station output constraint, and an electric quantity balance constraint, and a user may select all or part of the constraints according to specific planning requirements.
In this embodiment, the distribution network substation planning model is solved by using a particle swarm algorithm, the particle swarm algorithm is an evolutionary computing technique developed by j.kennedy and r.c.eberhart equal to 1995, and is derived from a simulation of a simplified social model, and is an intelligent algorithm for solving an optimal decision based on foraging of birds in a swarm, and the fast iterative optimization of the distribution network substation planning model is realized by using the particle swarm algorithm, so that the solving speed of the optimal scheme for distribution network substation planning is shortened, in this embodiment, the solving process by using the particle swarm algorithm is shown in fig. 3, and includes:
the method comprises the following steps: initializing the iteration times of the particle swarm algorithm, the population size speed of the particles and positions, wherein the positions are the number of charging piles of the distribution network transformer substation, the number of energy storage devices and the installation area of a photovoltaic panel on a garden roof and an open ground of the distribution network transformer substation;
step two: calculating the fitness corresponding to the current position of the particle according to a distribution network transformer substation planning model, determining the individual extreme value of the particle as the position of the particle with the minimum fitness in the previous k times of iterative calculation, and determining the global extreme value of the particle as the position of all the particles with the minimum fitness in the previous k times of iterative calculation;
step three: updating the speed and the position of the particles in the (k +1) th iterative computation based on the individual extreme value and the global extreme value;
step four: and repeating the second step to the third step until a preset iteration ending condition is met, and taking the global extreme value in the last iteration calculation as an optimal scheme.
Wherein the velocity of the particles is updated as:
v(k+1)＝ωv(k)+c1r1(pbest(k)-x(k))+c2r2(gbest(k)-x(k))；
the position of the particle is updated as:
x(k+1)＝x(k)+v(k+1)；
wherein v (k +1) is the velocity of the particle at the k +1 th iteration, v (k) is the velocity of the particle at the k-th iteration, ω is a preset inertia factor, c1、c2Are preset acceleration coefficients, r, of a particle swarm algorithm1、r2Pbest (k) is the individual extreme value of the particle in the previous k iterations, gbest (k) is the global extreme value of the particle in the previous k iterations, x (k +1) is the position of the particle at the k +1 th iteration, and x (k) is the position of the particle at the k-th iteration.
The optimal positions of the particles are solved through a particle swarm algorithm, the optimal charging pile number, the energy storage equipment number and the photovoltaic panel construction area of the distribution network transformer substation are obtained, the distribution network transformer substation constructed based on the optimal positions can meet various basic constraints, the benefit of the distribution network transformer substation is maximized, and the optimal multi-station fusion planning effect is achieved.
For example, a certain distribution network substation is selected to verify the method, and relevant parameters are shown in table 1.
TABLE 1
Solving the multi-station fusion substation planning model by using the particle swarm algorithm provided by S3, setting the maximum iteration number to be 1000 as an iteration end condition, and solving the optimal planning result as shown in Table 2:
TABLE 2
| Region(s) | Photovoltaic area/m2 | Number of energy storage tanks | Number of charging piles | Communication base station |
| Roof with a plurality of layers of material | 198.2 | - | - | 1 |
| Open space | 384.9 | 1 | - | - |
| Out-of-station area | - | - | 5 | - |
| Total of | 564.9 | 1 | 5 | 1 |
The current planning scheme yields annual revenue and equal-year-worth costs as shown in table 3. The photovoltaic maximizes the available area, the total output reaches 158kW, and the photovoltaic complete consumption is realized. Under the scene, the annual electricity saving cost reaches 14.2 ten thousand yuan, the annual cost of the optical storage and power station reaches 12.9 ten thousand yuan, and the charging pile earns 7.9 ten thousand yuan each year, so that the project profit is realized, the business expansion of electric vehicle charging, distributed photovoltaic and energy storage is ensured, and the advantage of the multi-station fusion intensive development concept is embodied.
TABLE 3
| Item | Photovoltaic + energy storage | Charging pile | Communication base station | Total of |
| Annual income | 14.2 | 7.9 | 0 | 22.1 |
| Equal annual cost | 12.9 | 4 | 1.5 | 18.4 |
In conclusion, the invention constructs various main targets including distributed photovoltaic, energy storage power stations and charging stations with the maximum annual yield as an objective function, and utilizes the particle swarm algorithm to calculate and analyze space distribution and economic benefit, selects the optimal scheme to select the scheme most suitable for the situation, and provides reference opinions for the implementation of multi-station fusion projects.
The sequence numbers in the above embodiments are merely for description, and do not represent the sequence of the assembly or the use of the components.
The above description is only exemplary of the present invention and should not be taken as limiting the invention, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A multi-station integrated distribution network transformer substation planning method is characterized by comprising the following steps:
constructing a distribution network transformer substation system integrating a charging pile, a photovoltaic panel and energy storage equipment;
according to the service life and the annual income of the distribution network transformer substation, the construction cost of the charging pile, the photovoltaic panel and the energy storage equipment is combined, a distribution network transformer substation planning model is constructed, and the constraint conditions of the distribution network transformer substation planning model are determined;
on the basis of a particle swarm algorithm, the planning model of the distribution network transformer substation is solved on the premise of meeting constraint conditions to obtain an optimal scheme of transformer substation planning, and the number of charging piles and energy storage equipment in the distribution network transformer substation and the installation area of a photovoltaic panel are set according to the optimal scheme.
2. The multi-station integrated distribution network and substation planning method according to claim 1, wherein a distribution network and substation planning model is constructed according to the service life and annual income of the distribution network and substation and in combination with the construction cost of charging piles, photovoltaic panels and energy storage devices, and comprises the following steps:
obtaining the service life Y and the discount rate r of the distribution network transformer substation, and calculating the equal-year-value coefficient of the distribution network transformer substation as phi:
with the maximum annual net income of the distribution network transformer substation as a target, establishing a distribution network transformer substation planning model as follows:
wherein F represents the annual net income of the distribution network transformer substation, I is the annual income of the distribution network transformer substation, CtotalFor the total construction cost of the distribution network transformer substation, D is the working days of the distribution network transformer substation, T is the total working time of the distribution network transformer substation every day, T represents the sampling time, delta T is the interval of the sampling time, P0,tThe power of the distribution network transformer substation for purchasing electricity from the power grid at the moment t, U is the unit price of the distribution network transformer substation for purchasing electricity from the power grid, n1E is the number of charging piles in the distribution network transformer substation, and e is the service unit price of the charging piles, PEV,tFor charging the output power of the pile at time t, tEVAverage operating time for charging piles, CEVConstruction costs for a single charging pile, CPVIs the photovoltaic panel construction cost per unit area, sPV,1For the construction area, s, of the photovoltaic panel on the roof of the park of the distribution network substationPV,2For the construction area, P, of the photovoltaic panel on the open ground of the garden of the distribution network substationESS,maxMaximum charge and discharge power of a single energy storage device, CESS,pCost per unit power of a single energy storage device, GmaxFor the installation capacity of a single energy storage device, CGCost per unit capacity, n, of a single energy storage device2For the number of energy storage boxes in the distribution network substation, CCS,1Construction costs of communication base stations on roofs, CCS,2For the construction costs of the communication base stations on open ground, BCSAs a valid variable, BCSIs 1 represents effective, BCSA value of 0 indicates no effect.
3. The method of claim 1, wherein the constraints of the distribution network and substation planning model comprise at least one of a construction area constraint, a charging station output constraint, and a power balance constraint.
4. The multi-station integrated distribution network and substation planning method according to claim 3, wherein the construction area constraint is as follows:
wherein s ispv,1For photovoltaic panel area, s, installed on the garden roof of a distribution network substationpv,2In order to fit the photovoltaic panel area of the garden open space of the distribution network substation,
is the unit floor space of the energy storage device,
for the unit area of the charging pile, n1For the number of energy storage devices in the distribution network substation, n2For the number of charging piles in the distribution network substation, S1Is the total area of the roof of the park, S2Is the total area of the open space of the park, S3For the out-of-station area, s, of the distribution network substationCS,1For the floor area of the communication base station on the roof, sCS,2Is the floor area of the communication base station on the air ground.
5. The multi-station fused distribution network substation planning method according to claim 3, wherein the charging station output constraints are:
0≤PEV,t≤PEV,max；
wherein, PEV,tFor charging the output power of the pile at time t, PEV,maxThe maximum rated output power of the charging pile.
6. The multi-station fused distribution network and substation planning method according to claim 3, wherein the electricity balance constraint is as follows:
P0,t+Pdch,t+PPV,t＝PEV,t+Pch,t；
wherein, P0,tPower, P, for distribution network substations purchasing electricity from the griddch,tFor discharge power of a single energy storage device at time t, PPV,tThe output of the photovoltaic panel at time t, PEV,tFor charging the output power of the pile at time t, Pch,tCharging power for a single energy storage device at time t.
7. The multi-station-fused distribution network and substation planning method according to claim 1, wherein the solving is performed on the distribution network and substation planning model on the premise that constraint conditions are met based on the particle swarm algorithm to obtain an optimal scheme for substation planning, and the method comprises the following steps:
the method comprises the following steps: initializing the iteration times of the particle swarm algorithm, the population size speed of the particles and positions, wherein the positions are the number of charging piles of the distribution network transformer substation, the number of energy storage devices and the installation area of a photovoltaic panel on a garden roof and an open ground of the distribution network transformer substation;
step two: calculating the fitness corresponding to the current position of the particle according to the distribution network transformer substation planning model, taking the position of the particle with the minimum fitness in the previous k times of iterative calculation as an individual extreme value of the particle, and taking the position of all the particles with the minimum fitness in the previous k times of iterative calculation as a global extreme value;
step three: updating the speed and the position of the particles in the (k +1) th iterative computation based on the individual extreme value and the global extreme value;
step four: and repeating the second step to the third step until a preset iteration ending condition is met, and taking the global extreme value in the last iteration calculation as an optimal scheme.
8. The multi-station fused distribution network substation planning method according to claim 7, wherein the third step comprises:
the velocity of the particle is updated as:
v(k+1)＝ωv(k)+c1r1(pbest(k)-x(k))+c2r2(gbest(k)-x(k))；
the position of the particle is updated as:
x(k+1)＝x(k)+v(k+1)；
wherein v (k +1) is the velocity of the particle at the k +1 th iteration, v (k) is the velocity of the particle at the k-th iteration, ω is a preset inertia factor, c1、c2Are preset acceleration coefficients, r, of a particle swarm algorithm1、r2Pbest (k) is the individual extreme value of the particle in the previous k iterations, gbest (k) is the global extreme value of the particle in the previous k iterations, x (k +1) is the position of the particle at the k +1 th iteration, and x (k) is the position of the particle at the k-th iteration.
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