CN116014810A - Optimal configuration method and system for optical storage system of grid distribution network - Google Patents

Abstract

The invention discloses a method and system for optimal configuration of a grid-based distribution network optical-storage system, including: grid-dividing the distribution network system; obtaining the average load and minimum standby power of each grid; The grid average load, the minimum standby power and the distributed optical storage optimization planning model are used to obtain the systematic optical storage configuration strategy. Constrained by power balance, node voltage, installed capacity of distributed photovoltaic nodes, the total amount of distributed photovoltaic installed in the distribution network, and energy storage battery capacity; through the Nash equilibrium method, the economy and reliability of the system's optical storage configuration strategy are balanced and analyzed. Obtain the optimal optical storage allocation strategy. Ensure the economy and stability of grid operation.

Description

A method and system for optimal configuration of a grid-based distribution network photovoltaic storage system

technical field

The invention relates to the technical field of optimal configuration of distribution network systems, in particular to a method and system for optimal configuration of gridded distribution network optical storage systems.

Background technique

The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

In recent years, with the maturity of photovoltaic power generation technology, more and more distributed photovoltaic power generation facilities have been applied to various nodes of the distribution network. Due to the characteristics of photovoltaic itself, its power generation is greatly affected by time and weather factors. Therefore, when it is connected to the grid, it will bring a series of uncertainties to the grid, such as local voltage exceeding the limit and large fluctuations in load power. Energy storage facilities have good electrical energy storage performance in a small area, sufficient charge and discharge power, and the ability to regulate the unevenness of power output in time and space, so the combined use of photovoltaics and energy storage can greatly promote the on-site consumption of renewable energy and improve Distributed Power Quality. In order to improve the overall safe and stable operation level of the distribution network in a certain area, it is necessary to plan the quantity and location of photovoltaics and energy storage in the context of gridding.

(1) Peng Chunhua of East China Jiaotong University and others proposed a planning method for distribution network photovoltaic-storage combined system based on source-network-load collaborative optimization. Based on the multi-scenario technology of parallel iterative binary K-means-+ clustering to deal with the uncertainty of distributed photovoltaics and loads, the establishment of a regional solar-storage joint system with the largest investor income, the largest photovoltaic on-site consumption rate and the average node voltage deviation The objective function with the minimum value is solved by using the parallel double quantum differential evolution algorithm. The results show that the proposed method can significantly improve the local consumption of distributed photovoltaics and increase the income of regional energy investors.

However, in this method, the coverage is relatively small for the planning scope of the optical storage system, and it is not suitable for planning and configuring optical storage in a large range.

(2) Wang Huimin from South China University of Technology and others proposed a distributed power planning method for active distribution networks based on a two-layer particle swarm optimization algorithm. Select wind turbines, photovoltaics and micro gas turbines as distributed power sources to be planned, take the minimum annual comprehensive cost as the objective function, and use various electrical quantities such as distributed power penetration rate, annual maximum load interruption, and distributed power installed capacity at nodes to be planned As a constraint condition, a distributed power generation planning model considering demand side response is established. Based on the idea of decomposition and coordination, the model is decomposed into planning layer and operation layer, and a two-layer particle swarm optimization algorithm is used to solve the problem.

This method only analyzes distributed power sources such as wind turbines and photovoltaics, and does not consider the configuration strategy of combining energy storage and power sources, which cannot solve the problem of low energy utilization of distributed power sources.

(3) Fan Zhicheng of Hohai University proposed a distributed power generation planning model for active distribution network considering fuzzy randomness. Aiming at the mismatch between distribution network power supply planning and grid structure, a typical daily scenario generation method is proposed considering the fuzzy randomness of DG output, and then the DG supplier's annual income is the largest and the distribution company's annual network loss is the lowest. For the upper and lower objective functions, a two-layer DG planning model of active distribution network is constructed. Finally, the planning model is solved by GAMS-DICOPT solver and discrete particle swarm optimization with adaptive weights.

This method takes into account the randomness of distributed power output, and uses the typical daily scene generation method to perform fuzzy simulation, solves it on the basis of the design objective function, and finally obtains the collaborative optimization results of distributed power and grid.

Method (1) After designing multiple objective functions, the optimal solution is solved, but the weight and distribution between multiple objectives are not clear, which makes the three aspects of investor income, photovoltaic on-site consumption rate and node voltage deviation Failed to get balanced. Method (2) does not consider the unified planning of distributed power generation and energy storage, so it is difficult to realize energy consumption on the spot, and it cannot solve the problem of low energy utilization rate of distributed power generation. The objective function designed by method (3) is mainly economical, and the reliability of distribution network operation is not considered enough, and the optimal configuration results may have low reliability.

Contents of the invention

In order to solve the above-mentioned problems, the present invention proposes a method and system for optimizing the configuration of grid-based distribution network optical storage systems. The grid is used as the object for planning and configuration of optical storage, which is conducive to the on-site consumption of photovoltaics. The influence of the distribution network will not spill over to the nearby grids, and when the grid is used as the object for planning and configuration of solar storage, an optimal planning model for distributed solar storage is established from the perspective of reliability and economy. After the storage optimization planning model obtains the systematic optical-storage allocation strategy, the reliability and economy of the allocation strategy are balanced by the Nash equilibrium method, and the optimal allocation strategy is selected to balance the economics and reliability of the optical-storage allocation. .

To achieve the above object, the present invention adopts the following technical solutions:

In the first aspect, a method for optimal configuration of grid-based distribution network solar-storage system is proposed, including:

Grid division of the distribution network system;

Obtain the average load and minimum reserve power of each grid;

According to the average load of each grid, the minimum standby power and the distributed photovoltaic storage optimization planning model, the system's photovoltaic storage configuration strategy is obtained. Among them, the distributed photovoltaic storage optimization planning model aims at economy and reliability, and uses power Electricity dynamic balance, power balance, node voltage, distributed photovoltaic node installation capacity, distribution network distributed photovoltaic installation total amount, and energy storage battery capacity are constraints;

Through the Nash equilibrium method, the economy and reliability of the system's optical-storage allocation strategy are balanced and analyzed, and the optimal optical-storage allocation strategy is obtained.

In the second aspect, an optimal configuration system for gridded distribution network photovoltaic storage system is proposed, including:

A grid division module for grid division of the distribution network system;

A demand acquisition module is used to obtain the average load and minimum reserve power of each grid;

The optical storage configuration strategy acquisition module is used to obtain the optical storage configuration strategy of the system according to the average load of each grid, the minimum standby power and the distributed optical storage optimization planning model, wherein the distributed optical storage optimization planning model is based on the economic Reliability and reliability are the goals, and the dynamic balance of power, power balance, node voltage, installed capacity of distributed photovoltaic nodes, total installed distributed photovoltaic distribution network, and energy storage battery capacity are constraints;

The optimal optical-storage allocation strategy acquisition module is used to perform a balanced analysis on the economy and reliability of the system's optical-storage allocation strategy through the Nash equilibrium method, and obtain the optimal optical-storage allocation strategy.

In the third aspect, an electronic device is proposed, including a memory, a processor, and computer instructions stored in the memory and run on the processor. When the computer instructions are run by the processor, a gridded distribution network is completed. The steps described in the optical storage system optimal configuration method.

In the fourth aspect, a computer-readable storage medium is provided for storing computer instructions, and when the computer instructions are executed by a processor, the steps described in a gridded distribution network optical storage system optimal configuration method are completed.

Compared with prior art, the beneficial effect of the present invention is:

1. The invention uses the grid as the object to plan and configure photovoltaic storage, which is conducive to the on-site consumption of photovoltaics, and the impact of the photovoltaic storage system on the distribution network will not spill over to nearby grids. In addition, different grids can be fully coordinated The relative independence of the grid can enable the solar storage system to compensate for the lack of power distribution in a targeted manner, ensuring the economy and stability of the grid operation.

2. The present invention establishes a distributed optical storage optimization planning model from the perspective of reliability and economy when carrying out optical storage planning and configuration with the grid as an object, and obtains the system optical storage configuration strategy through the distributed optical storage optimization planning model Finally, the reliability and economy of the allocation strategy are balanced through the Nash equilibrium method, and the optimal allocation strategy is selected to balance the economics and reliability of the optical storage allocation.

Advantages of additional aspects of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Description of drawings

The accompanying drawings constituting a part of the present application are used to provide further understanding of the present application, and the schematic embodiments and descriptions of the present application are used to explain the present application, and do not constitute improper limitations to the present application.

FIG. 1 is a flow chart of the method disclosed in Example 1.

Detailed ways:

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and/or combinations thereof.

Example 1

In this embodiment, a gridded distribution network optical storage system optimization configuration method is disclosed, as shown in Figure 1, including:

S1: Carry out grid division on the distribution network system.

The distribution network system is divided into grids, and the divided grids include urban grids, rural grids, industrial load grids, living load grids, plain area grids, and mountain and hill grids.

S2: Obtain the average load and minimum reserve power of each grid.

For the divided grid, the basic information of the grid is obtained, including the grid area, the type, quantity and topological connection relationship of the load nodes inside the grid, the capacity of the upper-level public substation, the total number of outgoing line intervals and the length of the line, and the geographical information in the grid etc., according to the basic information of the grids, the differences in the configuration conditions of photovoltaic energy storage between grids are analyzed, as shown in Table 1, and the demand for solar energy storage in different grids is obtained.

Table 1 Difference analysis of photovoltaic energy storage configuration conditions between grids

The demand of different grids for solar storage is measured by the comprehensive power loss probability value of the load nodes in the grid. For grids with a higher comprehensive power loss probability, distributed power sources such as optical storage can provide local power supply after the load node loses power to improve power supply reliability, and thus have a higher demand for optical storage. The minimum standby power refers to: In addition to the power delivered by the upper-level public substation inside each grid, the total power generation capacity of the local distributed power supply.

S3: According to the average load of each grid, the minimum standby power and the distributed optical storage optimization planning model, the system's optical storage configuration strategy is obtained. Among them, the distributed optical storage optimization planning model aims at economy and reliability. Constrained by the dynamic balance of electricity and power, power balance, node voltage, installed capacity of distributed photovoltaic nodes, total installed distribution network distribution width, and energy storage battery capacity.

The economic efficiency takes investment cost as the evaluation index, including the investment and construction cost of solar storage, the operation and maintenance cost of solar storage facilities, the cost of purchasing electricity from the large power grid, and the benefits of low energy storage and high power generation of energy storage batteries.

The overall economics of the distribution network is determined by the economics of each grid. In each grid, the investment and cost of distributed photovoltaics and energy storage are mainly in the early construction and operation and maintenance. For the overall distribution network, photovoltaic Savings investment can be expressed as:

表示光储投资建设成本，

表示光储设施运维成本，C_buy是从大电网的购电成本，C_pro是储能电池低储高发的收益。In the formula, C _eco is the total economic objective function,

Indicates the investment and construction cost of solar storage,

Indicates the operation and maintenance cost of solar storage facilities, C _buy is the cost of purchasing electricity from the large power grid, and C _pro is the income of energy storage batteries with low storage and high power generation.

和

表示单位容量的光伏、储能投资建设成本；N为网格数；

为第i个网格内的第j个光伏、储能电池的实际并网容量。In the formula, r ₀ is the discount rate, which is 0.06 here; y is the planning period, generally 20 years for distributed photovoltaics, and 10 years for energy storage batteries;

and

Indicates the investment and construction cost of photovoltaic and energy storage per unit capacity; N is the number of grids;

is the actual grid-connected capacity of the jth photovoltaic and energy storage battery in the ith grid.

为分布式光伏单位容量的弃电成本；

为第i个网格内的第j个光伏并网容量的理论值；

为从大电网购电的单位实时电价；

分别为各储能电池节点的充放电功率值。In the formula, λ is the conversion ratio of the operation and maintenance cost, where 0.1 is taken;

is the curtailment cost of distributed photovoltaic unit capacity;

is the theoretical value of the jth grid-connected photovoltaic capacity in the ith grid;

Real-time electricity prices for units that purchase electricity from large power grids;

are the charge and discharge power values of each energy storage battery node.

为光储节点的主网购电量。In the formula,

Purchase power for the main network of optical storage nodes.

分别为节点储能电池作用前后的负荷量。In the formula,

Respectively, the loads before and after the action of the node energy storage battery.

Reliability takes the total power failure loss as the evaluation index.

After accessing the optical storage system, the total power outage loss of the distribution network can be described as

分别为网格内负荷节点的每千瓦时停电损失和停电概率；S_i,j为负荷节点状态，0表示失电，1表示正常；P^i,j(t)表示节点实际消耗功率，定义为In the formula, C _loss is the reliability index of the distribution network, meaning the total outage loss; N _n is the number of load nodes in each grid;

are the power outage loss per kWh and power outage probability of the load nodes in the grid, respectively; S _i,j is the state of the load node, 0 means out of power, 1 means normal; P ^i,j (t) means the actual power consumption of the node, defined as

为节点功率需求；

为节点光储系统发出的功率。In the formula,

is the node power requirement;

is the power emitted by the node optical storage system.

Constraints include: power dynamic balance, power balance constraints, node voltage constraints, distributed photovoltaic node installation capacity constraints, distributed distribution network installation total constraints, and energy storage battery capacity constraints.

Among them, the dynamic balance of power and electricity is formula (8). The optical storage inside the grid should be consumed locally, the power will not overflow, and there will be no power gap. To achieve the dynamic balance of power and electricity, within the planning period:

P _trans +P _PV -P _load ≥P _spare (8)

In the formula, P _trans is the annual average power transmission of the superior public substation in the grid, PP _PV is the annual average power generation of the photovoltaic storage system in the grid, P _load is the annual average load in the grid, and P _spare is the grid during the planning period Minimum standby power.

The power balance constraint is formula (9).

In the formula, P _i , Q _i are the active power and reactive power of node i respectively; U _i , U _j are the voltages of nodes i and j respectively; B _ij , G _ij are the conductance, Susceptance; _θij is the voltage phase angle between nodes i and j.

The node voltage constraint is formula (10).

In the formula, U _i,min and U _i,max are the upper and lower limits of the voltage of node i respectively.

The installation capacity constraint of distributed photovoltaic nodes is formula (11).

为节点i安装光伏容量上限值。In the formula,

Install the PV capacity upper limit value for node i.

The total amount of distributed photovoltaic installation in the distribution network is constrained by formula (12).

In the formula, P _i ^load is the load power of node i; λ _PV is the proportional coefficient of distributed photovoltaic grid connection and the total load.

The energy storage battery is constrained by equations (13)-(15)

SOC _min ≤ SOC ≤ SOC _max (13)

0≤P _ES (t)≤P _ES-max (14)

分别为节点i储能电池充放电功率、安装容量的最大值。In the formula, SOC _min and SOC _max are the upper and lower limits of the state of charge of the energy storage battery respectively; P _ES-max ,

are the maximum charging and discharging power and installed capacity of the energy storage battery of node i, respectively.

Input the average load and the minimum standby power in each grid into the distributed optical storage optimization planning model constructed, and solve the model through the multi-objective genetic algorithm to obtain the system optical storage configuration strategy. The result is a series of optimal solutions The solution set formed by is reflected in the image as a curve, that is, the Prato curve.

S4: Through the Nash equilibrium method, the economy and reliability of the system's optical-storage allocation strategy are balanced and analyzed to obtain the optimal optical-storage allocation strategy.

In order to balance the influence of economy and reliability on the optimal solution, consider using the Nash equilibrium strategy. The Nash equilibrium method converts multiple objectives into a single objective, which can reflect the dimensional differences, magnitudes and probabilities of the two sides of the game. Applying this method to balance the objective functions of economy and reliability can take into account investment costs and power supply reliability. Based on this, the optimal solution for optical storage configuration is found. The Nash equilibrium objective function is represented by the formula:

max(u ₁ (x)-d ₁ )(u ₂ (x)-d ₂ )(16)

In the formula, u ₁ , u ₂ represent the direction of interests of the negotiating parties, and (d ₁ , d ₂ ) is the breaking point of the negotiation.

According to the invariance of linear transformation of Nash equilibrium, the optimization model of Nash equilibrium method can be expressed as:

In the formula, C refers to the objective function, c _eco and c _loss respectively refer to the two sides of the game, C _eco and C _loss are the reliability index and the economic index respectively, which are the loss margins of the two sides of the game.

The reliability and economy corresponding to the system's optical storage allocation strategy are input into the equilibrium optimization model (17) for solution, and the optimal optical storage allocation strategy is obtained.

The optimal optical-storage allocation strategy is selected by comprehensively considering the reliability and economy of the system. When the optimal optical-storage allocation strategy is used to configure the distribution network system, the reliability and economical efficiency of the optical-storage allocation are comprehensively improved.

This embodiment discloses a gridded distribution network optical storage system optimization configuration method, in order to propose an optical storage collaborative planning strategy in the context of distribution network gridding. In practice, there are multiple feeders in a distribution network in a region. However, the existing PV-storage planning strategy can only achieve the optimal configuration on a limited number of 10kV feeders, which will lead to problems such as the inability to consume PV locally and the voltage limit of adjacent lines. Studying the configuration of optical storage in units of blocks can effectively solve the above problems. Therefore, the method disclosed in this embodiment chooses to plan based on the gridded background. The grid distribution network has high power supply independence, and each grid has multiple feeders. Using these characteristics can effectively promote the consumption of photovoltaics on the spot and improve the reliability of power supply; build a balance between economy and reliability The grid-based distributed solar-storage optimization planning model takes the economics and reliability of the solar-storage system configured in the grid as the objective function, in which the overall economics of the distribution network is determined by the economics of each grid, and each network The investment in distributed photovoltaic and energy storage in Gezhong mainly depends on the preliminary construction and operation and maintenance, and the reliability is determined by the power outage loss during the planning period. The constraints include: dynamic balance of power and electricity, power balance, node voltage, photovoltaic installation capacity, Energy storage battery capacity, etc., the proposed grid-level photovoltaic configuration model can consider a variety of operating scenarios during the planning period, and has short-term and long-term adaptability; the game method is used to solve the multi-objective optimization problem of the photovoltaic storage system. In the distribution network, the access of optical storage facilities will greatly increase the reliability of nodes, but on the other hand, the investment will also increase accordingly, so a balance point needs to be found between reliability and economy. However, the solution method based on the combination of multi-objective genetic algorithm and Nash equilibrium disclosed in this embodiment first uses multi-objective genetic algorithm to obtain the Pareto curve, and then uses the Nash game method to find The balance point of economy and reliability, and finally improve the comprehensive index of the optical storage system connected to the distribution network.

This embodiment discloses a grid-based distribution network optical storage system optimization configuration method, which uses the power supply grid as a unit to plan and configure the number and location of the optical storage system, so that the overall distribution network in the region can operate economically. and power supply reliability are optimal. At the same time, grid-based planning and configuration of photovoltaic storage is conducive to the on-site consumption of photovoltaics. The impact of photovoltaic storage systems on distribution networks will not spill over to nearby grids. It can fully coordinate the demand for solar energy resources among different grids, and the relative independence of the grids can enable the solar storage system to compensate for the lack of power distribution in a targeted manner, ensuring the economy and stability of the grid operation.

Example 2

In this embodiment, a gridded distribution network optical storage system optimization configuration system is disclosed, including:

A grid division module for grid division of the distribution network system;

A demand acquisition module is used to obtain the average load and minimum reserve power of each grid;

The optical storage configuration strategy acquisition module is used to obtain the optical storage configuration strategy of the system according to the average load of each grid, the minimum standby power and the distributed optical storage optimization planning model, wherein the distributed optical storage optimization planning model is based on the economic Reliability and reliability are the goals, and the dynamic balance of power, power balance, node voltage, installed capacity of distributed photovoltaic nodes, total installed distributed photovoltaic distribution network, and energy storage battery capacity are constraints;

The optimal optical-storage allocation strategy acquisition module is used to perform a balanced analysis on the economy and reliability of the system's optical-storage allocation strategy through the Nash equilibrium method, and obtain the optimal optical-storage allocation strategy.

Example 3

In this embodiment, an electronic device is disclosed, including a memory, a processor, and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, a method disclosed in Embodiment 1 is completed. The steps described in a method for optimal configuration of a grid-based distribution network optical-storage system.

Example 4

In this embodiment, a computer-readable storage medium is disclosed, which is used to store computer instructions. When the computer instructions are executed by a processor, the optimization of a gridded distribution network optical storage system disclosed in Embodiment 1 is completed. Steps described in the configuration method.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the present invention can still be Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention shall fall within the protection scope of the claims of the present invention.

Claims (10)

1. The optimal configuration method for the optical storage system of the grid distribution network is characterized by comprising the following steps of:

grid division is carried out on the power distribution network system;

obtaining average load and minimum standby power of each grid;

obtaining a light storage configuration strategy of a system according to the average load, the lowest standby power and a distributed light storage optimization planning model of each grid, wherein the distributed light storage optimization planning model aims at economy and reliability, and is constrained by dynamic balance of electric power and electricity, power balance, node voltage, distributed photovoltaic node installation capacity, distribution network distributed photovoltaic installation total amount and energy storage battery capacity;

and carrying out balanced analysis on the economy and reliability of the optical storage configuration strategy of the system by using a Nash balancing method to obtain the optimal optical storage configuration strategy.

2. The optimal configuration method for the optical storage system of the meshed distribution network according to claim 1, wherein the grids partitioned by the system comprise urban grids, rural grids, industrial load grids, living load grids, plain grids and mountain hills grids.

3. The optimal allocation method for the optical storage system of the grid-type power distribution network according to claim 1, wherein the economy comprises optical storage investment construction cost, optical storage facility operation and maintenance cost, electricity purchasing cost from a large power grid and low storage and high-emission benefits of energy storage batteries.

4. The optimal configuration method for the optical storage system of the grid-type power distribution network according to claim 1, wherein the reliability takes total outage loss as an evaluation index.

5. The optimal configuration method for the optical storage system of the meshed distribution network according to claim 1, wherein the average load and the minimum standby power of each grid are determined according to the grid area, the types, the numbers and the topological connection relations of load nodes in the grid, the capacity of an upper public substation, the total number of outlet intervals and the line length, and geographic information in the grid.

6. The optimal configuration method for the optical storage system of the grid-type power distribution network according to claim 1, wherein average load and minimum standby power of each grid are input into a distributed optical storage optimal planning model, and the model is solved through a multi-objective genetic algorithm to obtain an optical storage configuration strategy of the system.

7. The optimization configuration method of the optical storage system of the grid-type power distribution network according to claim 1, wherein the equalization optimization model adopted when the economic and reliability of the optical storage configuration strategy of the system is subjected to equalization analysis by using the Nash equalization method optimization model is as follows:

wherein C denotes an objective function, C _eco 、c _loss Respectively refer to two game parties, C _eco 、C _loss The reliability index and the economical index are loss margins of two game parties respectively.

8. An optimal configuration system for an optical storage system of a grid-type power distribution network is characterized by comprising the following components:

the grid division module is used for carrying out grid division on the power distribution network system;

the demand acquisition module is used for acquiring the average load and the lowest standby power of each grid;

the optical storage configuration strategy acquisition module is used for acquiring an optical storage configuration strategy of the system according to the average load of each grid, the lowest standby power and the distributed optical storage optimization planning model, wherein the distributed optical storage optimization planning model aims at economy and reliability, and takes dynamic balance of electric power and electric quantity, power balance, node voltage, distributed photovoltaic node installation capacity, distributed photovoltaic installation total amount of a distribution network and energy storage battery capacity as constraints;

the optimal optical storage configuration strategy acquisition module is used for carrying out balanced analysis on the economy and reliability of the optical storage configuration strategy of the system through a Nash balancing method to obtain the optimal optical storage configuration strategy.

9. An electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the steps of a method as claimed in any one of claims 1 to 7.

10. A computer readable storage medium storing computer instructions which, when executed by a processor, perform the steps of a method as claimed in any one of claims 1 to 7.

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