CN-120474068-B - Optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage
Abstract
The invention relates to the technical field of new energy, and discloses an optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage, which comprises the steps of constructing a system architecture of rural distributed photovoltaic energy storage dispersed charge and storage and concentrated discharge; the method comprises the steps of setting a first constraint condition to target the maximum profit of the centralized aggregation type energy storage power station, setting a constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle, setting a second constraint condition to target the minimum sum of the cost of the mobile energy storage vehicle, the transportation cost of the traction trailer transportation mobile energy storage vehicle and the total cost of the distributed photovoltaic power station light discarding punishment cost, and sequentially carrying out iterative solution on the constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle and the optimal operation model of the mobile energy storage vehicle.
Inventors
- Xiong chu
- GONG KE
Assignees
- 重庆交通大学
Dates
- Publication Date
- 20260512
- Application Date
- 20250428
Claims (10)
- 1. An optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage is characterized by comprising the following steps: S1, constructing a system architecture of distributed photovoltaic energy storage, scattered charge, storage and centralized discharge of a village, wherein the system architecture comprises a mobile energy storage vehicle, a mobile power generation vehicle and a centralized aggregation type energy storage power station; s2, taking the maximum benefit of the centralized aggregation type energy storage power station as a target, setting a first constraint condition, and constructing a constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle, wherein the first constraint condition comprises node voltage constraint, tide constraint, branch active power constraint and user load demand constraint; S3, taking the minimum sum of the cost of the mobile energy storage vehicle, the transportation cost of the traction trailer for transporting the mobile energy storage vehicle and the total cost of the light discarding punishment cost of the distributed photovoltaic power station as a target, and setting a second constraint condition to construct an optimized operation model of the mobile energy storage vehicle, wherein the second constraint condition comprises the constraint of the charge and discharge power of the mobile energy storage vehicle and the constraint of the capacity of the mobile energy storage vehicle; And S4, sequentially carrying out iterative solution on the constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle and the optimized operation model of the mobile energy storage vehicle so as to realize the optimal configuration of the mobile energy storage vehicle and the mobile power generation vehicle.
- 2. The optimization method for improving rural photovoltaic absorption capacity by utilizing mobile energy storage according to claim 1, wherein the system architecture of rural distributed photovoltaic energy storage scattered charge, storage and concentrated discharge further comprises a rural distributed photovoltaic power station and an energy monitoring management system.
- 3. The optimization method for improving rural photovoltaic power consumption by utilizing mobile energy storage according to claim 2, wherein step S2 specifically comprises: S21, constructing an objective function of the maximum benefit of the centralized aggregation type energy storage power station, namely: Wherein, the Indicating that the maximum value is taken, Represents the benefits of a centralized aggregated energy storage power station, Represents the electricity selling benefits obtained by the centralized aggregation type energy storage power station through the discharge of the distribution network, Represents the selling income of the centralized aggregation type energy storage power station leasing to the mobile energy storage vehicle of the user for providing discharge for the user, Indicating the benefits of improving the utility of the distribution equipment asset, Indicating the length of the run of a day, Represent the first The trade electricity price of the centralized energy storage power station and the distribution network is concentrated at any moment, Represent the first The transaction electric quantity of the aggregation type energy storage power station and the distribution network is concentrated at all times, Representing the cost of a single inverter and, Indicating the number of mobile energy storage vehicles, Represent the first Time-moving energy storage vehicle Is used for the electric power of the (a), Indicating the number of users who need to rent the mobile energy storage vehicle, Represent the first The time centralized aggregation type energy storage power station rents the trade electricity price of the mobile energy storage vehicle to the user, Represent the first Time of day user I.e. the electric power of the mobile power generation car; S22, constructing node voltage constraint, namely: Wherein, the Representing the node voltage constraint, 、 Representing nodes in a distribution network At the allowable voltage minimum and voltage maximum, Representing nodes in a power distribution network The voltage at which the voltage is applied, Representing nodes in a power distribution network The phase angle at which the phase angle is at, 、 Representing nodes in a distribution network A phase angle minimum value and a phase angle maximum value; s23, constructing tide constraint, namely: Wherein, the Representing the constraint of the power flow, 、 Representing nodes in a power distribution network Is used for the active injection and the reactive injection, Representing nodes in a power distribution network The voltage at which the voltage is applied, Representing nodes And node Whether there is a direct electrical connection between them, 、 Representing nodes respectively And node The resistance and the reactance of the branch circuit, The representation of a sinusoidal function is given, Representing a cosine function of the sign of the signal, Representing nodes And node Phase angle difference between; s24, constructing branch active power constraint, namely: Wherein, the Representing the active power constraint of the branch, Represent the first The maximum active power of the branch circuit, Represent the first Time of day (time) The actual active power of the branch circuit; s25, constructing user load demand constraints, namely: Wherein, the Representing the constraints of the load demand of the user, Represent the first Time of day user Is not required by the load; s26, constructing a constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle, namely: 。
- 4. the optimization method for improving rural photovoltaic power consumption by using mobile energy storage according to claim 3, wherein step S3 specifically comprises: S31, calculating the cost of the mobile energy storage vehicle, namely: Wherein, the Indicating the cost of the mobile energy storage vehicle, Represents the investment and construction costs of the energy storage battery, Indicating the operation and maintenance costs of the energy storage battery, Represents the charge and discharge costs of the energy storage battery, Representing the cost per unit power of the energy storage cell, Indicating mobile energy storage vehicle Is used for the electric power of the (a), Representing the cost per unit capacity of the energy storage cell, Indicating mobile energy storage vehicle Is provided with a configuration capacity of (a), The rate of the discount is represented by the value of the discount, Indicating the life span of the energy storage cell, Represents the operational cost of annual energy production of the energy storage cell, Represents the annual energy production of the energy storage battery, Represent the first The electricity purchase price of the energy storage battery is changed at any time, Represent the first The electricity selling price of the energy storage battery is kept at all times, 、 Respectively represent the first Time-moving energy storage vehicle Charging power and discharging power of (a); s32, calculating the transportation cost of the traction trailer for transporting the movable energy storage vehicle, namely: Wherein, the Representing the transportation cost of the traction trailer for transporting the mobile energy storage vehicle, Represent the first The unit transportation cost of the mobile energy storage vehicle for transporting the trailer is drawn at any time, Represent the first The transport distance at the moment; s33, calculating the cost of the light discarding penalty of the distributed photovoltaic power station, namely: Wherein, the Represents the cost of the light discarding penalty of the distributed photovoltaic power station, Represents the light-discarding penalty coefficient, Represent the first The photovoltaic power generation amount is generated at the moment, Represent the first The charging power of the energy storage vehicle is moved at any time; s34, constructing the charge and discharge power constraint of the mobile energy storage vehicle, namely: Wherein, the Represents the charge and discharge power constraint of the mobile energy storage vehicle, 、 Respectively represent the first The charging efficiency and the discharging efficiency of the energy storage vehicle are moved at any time, Represent the first The discharge power of the energy storage vehicle is moved at any time, 、 Respectively represent the first The charging state and the discharging state of the energy storage vehicle are moved at any time, 、 Respectively representing the maximum charging power and the maximum discharging power of the movable energy storage vehicle; s35, constructing capacity constraint of the mobile energy storage vehicle, namely: Wherein, the Representing a capacity constraint of the mobile energy storage vehicle, Represent the first The configuration capacity of the energy storage vehicle is moved from time to time, Represent the first The configuration capacity of the energy storage vehicle is moved from time to time, 、 Representing the minimum configuration capacity and the maximum configuration capacity of the mobile energy storage vehicle respectively, 、 Respectively represent the first The minimum and maximum energy storage factors of the energy storage vehicle are moved at any time, Representing the capacity of the mobile energy storage vehicle; S36, taking the minimum sum of the cost of the mobile energy storage vehicle, the transportation cost of the traction trailer for transporting the mobile energy storage vehicle and the total cost of the light discarding punishment cost of the distributed photovoltaic power station as a target, and constructing an optimized operation model of the mobile energy storage vehicle based on the capacity constraint of the mobile energy storage vehicle and the charge and discharge power constraint of the mobile energy storage vehicle, namely: Wherein, the The representation takes the minimum value of the value, The total cost of the cost of the mobile energy storage vehicle, the transportation cost of the traction trailer for transporting the mobile energy storage vehicle and the cost of the light discarding punishment of the distributed photovoltaic power station is represented.
- 5. The optimization method for improving rural photovoltaic power consumption by using mobile energy storage according to claim 4, wherein step S4 specifically comprises: s41, taking a constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle as an outer layer model, and taking an optimized operation model of the mobile energy storage vehicle as an inner layer model; s42, carrying out gene coding by adopting a random global search optimization method, and simultaneously carrying out optimization solution on an outer layer model by combining a tide calculation tool; S43, optimizing and solving the inner layer model by adopting a particle swarm method; And S44, calculating an objective function difference value of the outer layer model and the inner layer model, judging whether the objective function difference value is smaller than the transformation cost of the power distribution network when energy storage logistics are not considered or whether the outer layer model is subjected to optimization solution to reach the maximum iteration times, if so, outputting an optimal solution of the electric power of the mobile energy storage vehicle and the mobile power generation vehicle and the configuration capacity of the mobile energy storage vehicle, otherwise, continuing to execute the step S42.
- 6. The method for optimizing rural photovoltaic power consumption by mobile energy storage according to claim 5, wherein step S42 specifically comprises: S421, setting a first input parameter which comprises photovoltaic power generation amount, load demands of users, transaction electricity prices of a centralized aggregation type energy storage power station and a power distribution network, single inverter cost, unit transportation cost of a traction trailer transportation mobile energy storage vehicle and a light discarding punishment coefficient; s422, setting random global search optimization method parameters, which comprise population scale, first maximum iteration times, cross rate and variation rate; S423, encoding the electric power of the mobile energy storage vehicle, the configuration capacity of the mobile energy storage vehicle and the electric power of the mobile power generation vehicle into chromosomes; s424, calculating an objective function value of the outer layer model, namely: ; s425, taking the objective function value of the outer layer model as the fitness of the chromosome, and performing iterative optimization.
- 7. The method for optimizing rural photovoltaic power consumption by mobile energy storage according to claim 6, wherein step S425 specifically comprises: s4251, initializing a population, and randomly generating a plurality of groups of candidate solutions; s4252, calculating power flow parameters of the power distribution network by using a power flow calculation tool, judging whether node voltage constraint, power flow constraint, branch active power constraint and user load demand constraint are met, if yes, executing a step S4253, otherwise, executing a step S4251; s4253, calculating the objective function value of the outer layer model again, taking the objective function value as the fitness of the chromosome, and simultaneously selecting individuals with high fitness to perform intersection and mutation; and S4254, repeating the steps S4252-S4253, and obtaining the optimal electric power of the mobile energy storage vehicle, the configuration capacity of the mobile energy storage vehicle and the electric power of the mobile power generation vehicle if the first maximum iteration number is reached.
- 8. The method of optimizing rural photovoltaic power consumption utilizing mobile energy storage according to claim 7, wherein the power flow parameters of the power distribution network in step S4252 comprise voltage, phase angle, active injection, reactive injection, and actual active power of the branch.
- 9. The optimizing method for improving rural photovoltaic power consumption by using mobile energy storage according to claim 8, wherein step S43 specifically comprises: s431, setting a second input parameter which comprises electricity purchasing price and electricity selling price of an energy storage battery, charging efficiency and discharging efficiency of a mobile energy storage vehicle, optimal electric power of the mobile energy storage vehicle, configuration capacity of the mobile energy storage vehicle and electric power of a mobile power generation vehicle, wherein the optimal electric power is transmitted by an outer layer model; S432, setting particle swarm method parameters, which comprise particle numbers, a second maximum iteration number, a first learning factor and a second learning factor; s433, calculating an objective function value of the inner layer model, namely: ; s434, taking the objective function value of the inner layer model as the cost value of each particle, and performing iterative optimization.
- 10. The method for optimizing rural photovoltaic power generation by mobile energy storage of claim 9, wherein step S434 specifically comprises: S4341, initializing a particle swarm, and randomly generating charging power, discharging power, a charging state and a discharging state of the mobile energy storage vehicle; s4342, judging whether the charging power, the discharging power, the charging state and the discharging state of the mobile energy storage vehicle meet the capacity constraint of the mobile energy storage vehicle and the charging and discharging power constraint of the mobile energy storage vehicle, if yes, executing step S4343, otherwise, executing step S4343 after correcting the objective function value of the inner layer model or directly correcting the upper limit and the lower limit of the capacity constraint of the mobile energy storage vehicle and the upper limit of the charging and discharging power constraint of the mobile energy storage vehicle by using a punishment function; S4343, calculating the cost value of each particle again, updating the individual optimal solution and the global optimal solution to adjust the charging power, the discharging power, the charging state and the discharging state of the movable energy storage vehicle, and if the variation of the objective function value of the inner layer model in the current iteration and the last iteration is smaller than a preset threshold value, converging the objective function to obtain the optimal charging power and the discharging power of the movable energy storage vehicle and the optimal objective function value of the inner layer model.
Description
Optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage Technical Field The invention relates to the technical field of new energy, in particular to an optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage. Background Currently, rural distributed photovoltaic power stations generally exhibit the characteristics of small capacity, large quantity and distributed configuration, which brings about a series of problems. Firstly, because a single photovoltaic power station needs to independently configure an inverter, the system cost is obviously increased due to long idle time of the capacity of the inverter, and secondly, the mismatch between the photovoltaic power generation and the power load exists in time and space, the excessive electric energy is difficult to effectively store and utilize, and the light discarding is easy to occur. Meanwhile, the decentralized photovoltaic power station is difficult to participate in the electric power market in a large scale, the internet surfing is difficult, the spontaneous self-use income mode is single, and the economic benefit is limited. In addition, the rural low-voltage distribution network line is longer and radial, the phenomenon that the voltage is too low frequently occurs on part of the low-voltage side in the electricity consumption peak period, the problem of voltage quality is prominent, the load cannot normally operate, and the power supply reliability is reduced. In summary, the prior art is difficult to meet the requirement of utilizing a large amount of rural photovoltaic resources. Although the fixed energy storage is configured to absorb the photovoltaic electric quantity in daytime, the rural power distribution network has weak structure, low transmission capacity and large transformation investment of the power distribution network, and power grid enterprises lack of investment will, so that the photovoltaic electric quantity absorbed by a large amount of energy storage is difficult to absorb by on-site load under the condition of difficult online sales. In addition, there are many non-stationary electric sites in rural areas, such as agricultural product harvesting, processing, temporary irrigation, etc., where there is often no power supply line or facility, and there is a great need for flexible mobile power supplies. Disclosure of Invention Aiming at the defects in the prior art, the invention provides an optimization method for improving rural photovoltaic absorption capacity by utilizing mobile energy storage, namely, a distributed photovoltaic electric quantity is absorbed by an energy storage trolley, then a centralized aggregation distribution mode is formed, one part of the distributed photovoltaic electric quantity is integrated and connected to a power grid for discharging and selling, and the other part of the distributed photovoltaic electric quantity is uniformly scheduled and distributed to a temporary electricity utilization load point. The photovoltaic scale is enlarged, the photovoltaic resource profit capability in rural areas is increased, the problem that part of electricity utilization points are unavailable due to no line facilities or electricity cannot be used due to voltage quality problems is solved, and the purposes of increasing the income and protecting the supply by using the distributed photovoltaic are achieved. In order to achieve the aim of the invention, the invention adopts the following technical scheme: An optimization method for improving rural photovoltaic digestion capacity by utilizing mobile energy storage comprises the following steps: S1, constructing a system architecture of distributed photovoltaic energy storage, scattered charge, storage and centralized discharge of a village, wherein the system architecture comprises a mobile energy storage vehicle, a mobile power generation vehicle and a centralized aggregation type energy storage power station; s2, taking the maximum income of the centralized aggregation type energy storage power station as a target, setting a first constraint condition, and constructing a constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle; S3, taking the minimum sum of the cost of the mobile energy storage vehicle, the transportation cost of the traction trailer for transporting the mobile energy storage vehicle and the total cost of the light discarding punishment cost of the distributed photovoltaic power station as a target, setting a second constraint condition, and constructing an optimized operation model of the mobile energy storage vehicle; And S4, sequentially carrying out iterative solution on the constant volume model of the mobile energy storage vehicle and the mobile power generation vehicle and the optimized operation model of the mobile energy storage vehicle so as to realize the optimal configuration of the mobi