Loss reduction optimization method for power distribution network containing distributed photovoltaic

Abstract

The invention discloses a distributed photovoltaic power distribution network loss reduction optimization method, and belongs to the technical field of energy systems. Comprising the following steps: establishing a double-layer loss reduction optimization model of a distribution network level and a regulation level; and solving the double-layer loss reduction optimization model by using an improved genetic algorithm and a particle swarm optimization algorithm. According to the method, the influence of distributed photovoltaic grid connection on the power distribution network loss is comprehensively considered, corresponding comprehensive optimization loss reduction measures are put forward in combination with the actual situation of the power distribution network, the problem that the power distribution network loss is increased due to intermittency and volatility of photovoltaic output power is solved, collaborative development of photovoltaic and the power distribution network can be promoted, the economic operation level of the power distribution network is improved, and the economic benefit of the power distribution network is improved. And energy conservation and emission reduction of the power distribution network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy systems, and in particular to a method for optimizing loss reduction in a distribution network containing distributed photovoltaics. Background Art

[0002] Under the premise of a simple distribution network structure and a small number of photovoltaic grid-connected units, the active power loss of the distribution network can be effectively reduced by reasonably optimizing the location of the grid connection point. However, with the change in the nature of the distribution network load and the increasing complexity of the distribution network structure, the impact of photovoltaic grid connection on the distribution network is becoming increasingly difficult to analyze. On the one hand, the integration of photovoltaic power sources can provide reactive power and voltage support, thereby helping to improve the power quality of the distribution network and reduce losses. However, on the other hand, if the photovoltaic grid-connected location is unreasonable and the grid-connected capacity is not appropriate, it is difficult to play a role in reducing losses, and even increase the network loss of the distribution network. One of the common means of limiting losses in traditional distribution networks is to optimize the flow by reasonably adjusting the operating mode. However, now that the distribution network has the access of distributed power sources and the user load is complex, the flow control of the distribution network has become very difficult. Electric energy storage technology can solve problems such as the intermittent nature of distributed power generation, but energy storage technology is still immature and cannot store large-scale electric energy, so power generation and power consumption are still highly simultaneous.

[0003] Therefore, a loss reduction optimization method for distribution networks containing distributed photovoltaics is needed to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method for optimizing loss reduction in a distribution network containing distributed photovoltaics, comprising:

[0005] Establish a two-layer loss reduction optimization model at the distribution network level and the control level;

[0006] The double-layer loss reduction optimization model is solved using improved genetic algorithm and particle swarm algorithm.

[0007] The loss reduction optimization model at the distribution network level includes:

[0008] Objective function:

[0009]

[0010] Wherein, ΔP and F represent the active power loss of the distribution network and the unit cost converted into electricity charges respectively; M, L, N represent the distribution transformer installed with parallel capacitor bank compensation, the modified line, and the collection of the modified transformer respectively, i, j, n is one of them, Q i represents the reactive power compensation capacity of the shunt capacitor on the low voltage side of the i-th distribution transformer, L j represents the length of the replaced line j, S n Indicates the capacity of the distribution transformer, fq 、f l 、f b They represent the investment cost of shunt capacitor bank compensation, and the cost of line and distribution transformer transformation respectively;

[0011] Constraints:

[0012] Node voltage upper and lower limit constraints

[0013] U min ≤U i ≤U max

[0014] Where U i is the voltage of load node i; U max , U min are the upper and lower limits of the voltage amplitude at node i;

[0015] Branch current inequality constraints

[0016] I j ≤I jmax ,j=1,2,...,n n

[0017] Among them, I jmax represents the maximum transmission current of line j; n n Indicates the total number of branches in the distribution network.

[0018] The loss reduction optimization model at the regulatory level includes:

[0019] Objective function:

[0020] f(X)=MIN∑P loss

[0021] Among them, X is the set of all loss reduction measures of the control layer, expressed as [Q DG ,Q C ,D], that is, the adjustable distributed photovoltaic reactive output Q connected to the 10kV busbar of the distribution network DG , the reactive compensation capacity Q of the switchable capacitor bank C , transformer adjustable tap position D; ∑P loss It is the active power loss of the network after adopting the loss reduction measures at the distribution network control layer;

[0022] Constraints:

[0023] Node Voltage Constraints

[0024] U min ≤U i ≤U max

[0025] Where U iis the voltage of bus node i; U max , U min is the upper and lower limits of the node voltage amplitude;

[0026] Capacitor bank compensation capacity constraints

[0027] Q Cmin ≤Q C ≤Q Cmax

[0028] In the formula, Q Cmax It means that when all capacitor banks are put into operation, there is the maximum reactive power compensation capacity, Q Cmin Represents the constraint on the minimum compensation capacity of the capacitor bank.

[0029] The specific steps of solving the double-layer loss reduction optimization model using the improved genetic algorithm and particle swarm algorithm are as follows:

[0030] Step 1: Initialize the distribution network and algorithm related parameters;

[0031] Step 2: Perform relevant genetic operations of genetic algorithm;

[0032] Step 3: Calculate the fitness function value of each gene;

[0033] Step 4: Improve the particle swarm algorithm and calculate the fitness function value of each particle;

[0034] Step 5: Determine whether the particle swarm algorithm converges, if yes, go to step 6; if no, go to step 4;

[0035] Step 6: Determine whether the genetic algorithm converges, if yes, go to step 7; if no, go to step 2;

[0036] Step 7: Output the model calculation results and the model solution is completed.

[0037] The beneficial effects of the present invention are:

[0038] The present invention comprehensively considers the impact of distributed photovoltaic grid-connected power on the network loss of the distribution network, and proposes corresponding comprehensive optimization loss reduction measures based on the actual situation of the distribution network, thereby overcoming the problem of increased network loss caused by the intermittent and fluctuating photovoltaic output power. It can promote the coordinated development of photovoltaic and distribution networks, improve the economic operation level of the distribution network, and enhance energy conservation and emission reduction of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of the method for optimizing the loss reduction of a distribution network including distributed photovoltaics according to the present invention;

[0040] Figure 2 It is the relationship curve between transformer loss and load rate;

[0041] Figure 3 Optimize topology for photovoltaic input location;

[0042] Figure 4 This is a comparison chart of PV1 output active power after implementing loss reduction measures;

[0043] Figure 5 This is a comparison chart of PV1 output reactive power after implementing loss reduction measures. DETAILED DESCRIPTION

[0044] The present invention provides a method for optimizing loss reduction in a distribution network including distributed photovoltaics, which will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0045] Figure 1 The flowchart of the method for optimizing the loss reduction of a distribution network including distributed photovoltaic power generation according to the present invention specifically includes:

[0046] 1. Establish a two-layer loss reduction optimization model at the distribution network level and the control level:

[0047] Comprehensive analysis of all loss reduction technical measures in the distribution network shows that they can be divided into two categories based on the content of loss reduction implementation. One category involves changing the structure or network parameters of the distribution network, such as replacing conductors, optimizing power supply paths, replacing distribution transformers, configuring reactive power compensation, etc. These measures can be understood as static measures implemented at the distribution network level. The other category involves the operating conditions of the distribution network, such as changing the on-load tap position of the main transformer, automatically switching parallel capacitor banks, and regulating the output of distributed photovoltaics. These measures can be understood as dynamic measures implemented at the control level. Therefore, a double-layer loss reduction optimization model at the distribution network level and the control level is adopted.

[0048] Distribution network level: Regarding the distribution network loss, the distribution network grid structure has the greatest impact on the network loss, and this feature is more obvious in the medium voltage distribution network. For the 10kV voltage level distribution network, the loss expression of each component is:

[0049]

[0050] Two conclusions can be drawn from formula (1): First, the greater the current flowing through the distribution network, the greater the loss, and the loss is proportional to the square of the current; second, the resistance of the component itself also affects the loss. The greater the resistance, the greater the loss, and the two are proportional.

[0051] According to the factors affecting the loss and the laws of these factors, guide the formulation of relevant measures to reduce the network loss of the distribution network:

[0052] 1) Increase the cross-sectional area of ​​the wire. According to the resistance expression of the wire It can be seen that increasing the cross-sectional area S can reduce the line resistance, thereby reducing the line loss. According to formula (1), the larger the line cross-sectional area, the smaller the resistance and the smaller the loss, but the larger the cross-sectional area of ​​the wire also means higher cost.

[0053] 2) Reduce the power supply radius. From the resistance expression of the conductor, we know that another way to reduce the line resistance is to reduce the line length L. Therefore, by improving and optimizing the grid structure and reducing the power supply radius, we can effectively achieve the purpose of reducing losses.

[0054] 3) Eliminate distribution transformers with outdated performance. On the one hand, traditional transformers are outdated and can no longer be applied to the current distribution system. On the other hand, they are generally used for a long time and their performance has declined, so the loss of these transformers is usually relatively large. Replacing them with advanced technology design and manufacturing can greatly reduce the no-load loss of transformers.

[0055] 4) Optimize the configuration of distribution transformer capacity. The load size of the transformer will affect its loss. According to a large amount of operating data, the transformer has the highest operating efficiency and the lowest power loss when the load rate is between 40% and 75%. When the transformer load rate is less than 30% or more than 85%, the loss will increase significantly. Figure 2 This is the relationship curve between transformer loss and load rate.

[0056] 5) Reactive power optimization compensation. In addition to consuming active power, the inductive components of the distribution line also absorb reactive power. If the reactive power absorbed by these inductive components is too large, the system will be insufficient in reactive power, causing the system voltage to drop, which will further increase the active power loss of the system. To solve this problem, on the one hand, the reactive power output of the system can be increased, and on the other hand, capacitive reactive power compensation can be performed on site to improve the power factor of the system. Among them, reactive power compensation has the advantages of simple implementation and low cost, and is widely used in distribution networks.

[0057] Taking into account the loss reduction benefits of the distribution network, the investment cost of the shunt capacitor bank compensation on the low side of the distribution transformer, and the transformation cost of the line and distribution transformer, the objective function of the loss reduction optimization model at the distribution network layer is obtained as follows:

[0058]

[0059] Wherein, ΔP and F represent the active power loss of the distribution network and the unit cost converted into electricity charges respectively; M, L, N represent the distribution transformer installed with parallel capacitor bank compensation, the modified line, and the collection of the modified transformer respectively, i, j, n is one of them, Q i represents the reactive power compensation capacity of the shunt capacitor on the low-voltage side of the i-th distribution transformer, L j represents the length of the replaced line j, S n Indicates the capacity of the distribution transformer, fq 、f l 、f b They represent the investment cost of shunt capacitor bank compensation and the transformation cost of lines and distribution transformers respectively.

[0060] Constraints:

[0061] 1. Node voltage upper and lower limit constraints

[0062] The voltage at each node of the distribution line should be maintained within a safe range and should not be too high or too low, that is:

[0063] U min ≤U i ≤U max (3)

[0064] Where U i is the voltage of load node i; U max , U min are the upper and lower limits of the voltage amplitude at node i.

[0065] 2. Branch current inequality constraints

[0066] Any 10kV distribution line has a maximum transmission power limit, usually expressed as the maximum transmission current, that is:

[0067] I j ≤I jmax ,j=1,2,...,n n (4)

[0068] Among them, I jmax represents the maximum transmission current of line j; n n Indicates the total number of branches in the distribution network.

[0069] Regulation level: Reactive compensation can effectively reduce losses, but in order to reduce costs and reduce operation and maintenance expenses, current reactive compensation equipment generally uses parallel capacitor banks, which are not always in a compensation state and can only be switched according to changes in reactive load. At the same time, the main transformer often has multiple taps, which can be adjusted according to voltage and reactive conditions. Therefore, in traditional distribution networks, the equipment that can participate in economic operation regulation is the 10kV parallel capacitor bank and the 110kV main transformer tap; and in distribution networks containing distributed photovoltaics, distributed photovoltaic active and reactive output regulation and other measures have been added.

[0070] (1) Automatic load adjustment of main transformer tap changer

[0071] For a specific component, when the impedance remains unchanged, the higher the voltage, the greater the active power consumed, and the consumption is proportional to the square of the voltage. Therefore, under a specific grid structure, the goal of reducing losses can be achieved by adjusting the grid voltage. The main transformers of 35kV and above voltage levels generally have the ability to adjust the taps on load, and can automatically adjust the gear position under load.

[0072] (2) Automatic switching of 10kV parallel capacitor banks

[0073] According to the location and capacity of reactive power compensation, it can be divided into centralized compensation and decentralized compensation. Centralized compensation means that the reactive power compensation device is installed uniformly on the low-voltage side of the transformer, while decentralized compensation means that the reactive power compensation device is installed decentralized near the user's transformer, which belongs to on-site compensation. These two methods have their own advantages and disadvantages and scope of application. Centralized compensation is easier to install and control, but the effect is poor; decentralized compensation has better compensation effect, but it is more troublesome to install and control.

[0074] In a substation, one or two parallel capacitor groups are generally installed on the 10kV bus. These two capacitor groups can be automatically adjusted based on the reactive power and voltage conditions. The current voltage and reactive power regulation strategy is generally based on the nine-square diagram or the extended nine-square diagram (seventeen-zone diagram).

[0075] (3) Regulation of active and reactive power output of distributed photovoltaics

[0076] In a distribution network containing distributed photovoltaics, the active and reactive power output of photovoltaics affects the power flow distribution of the distribution network, and the power flow distribution directly affects the size of active power loss. Therefore, the size of the distribution network loss can be adjusted by regulating the active and reactive power output of distributed photovoltaics.

[0077] Generally speaking, when distributed photovoltaics are connected to the distribution network, the inverter is required to have the ability to continuously adjust reactive power between the power factor leading 0.98 and lagging 0.98. In fact, the inverter has a reactive output adjustment range of leading 0.95 to lagging 0.95. Therefore, distributed photovoltaics have a large reactive output capacity and can also be included in the list of loss reduction optimization measures.

[0078] The loss reduction measures at the distribution network control layer do not require the installation of new equipment or the replacement of old equipment, and do not need to consider the issue of additional investment costs. Therefore, the objective function can only be the minimum distribution network loss, and its mathematical expression is:

[0079] f(X)=MIN∑P loss (5)

[0080] Among them, X is the set of all loss reduction measures of the control layer, which can be expressed as [Q DG ,QC ,D], that is, the adjustable distributed photovoltaic reactive output Q connected to the 10kV busbar of the distribution network DG , the reactive compensation capacity Q of the switchable capacitor bank C , the transformer can be adjusted to tap position D, among which only Q DG is a floating-point variable, and the other two are integer variables; ∑P loss It is the active power loss of the network after adopting the above-mentioned loss reduction measures at the distribution network control layer.

[0081] Constraints:

[0082] 1. Node voltage constraints

[0083] Similarly, all bus voltages in the distribution network should be maintained within an allowable range, namely:

[0084] U min ≤U i ≤U max (6)

[0085] Where U i is the voltage of bus node i; U max , U min are the upper and lower limits of the node voltage amplitude.

[0086] 2. Constraints on compensation capacity of capacitor banks

[0087] Since the capacitor bank has only two states, namely, switched on and switched off, the compensation capacity of the parallel capacitor bank on the 10kV bus is not a continuous variable. However, when all capacitor banks are switched on, there is the maximum reactive power compensation capacity, expressed as Q Cmax Indicates that there is also a constraint on the minimum compensation capacity of the capacitor bank, expressed as Q Cmin If , then the constraint can be expressed as:

[0088] Q Cmin ≤Q C ≤Q Cmax (7)

[0089] 2. Solve the double-layer loss reduction optimization model using improved genetic algorithm and particle swarm algorithm:

[0090] The specific process of the solution algorithm is as follows:

[0091] 1. Improvement of Genetic Algorithm

[0092] The traditional genetic algorithm uses binary coding. Since it is only 0.1, as the scale of the problem increases, the algorithm's computing power performance is revealed, so improvements have been made to the coding method.

[0093] (1) Off-diagonal elements

[0094] The off-diagonal elements in the matrix represent the connections between nodes, so they are used to represent the wires and models between nodes.

[0095] (2) Elements on the diagonal

[0096] The elements on the diagonal of the matrix usually represent the capacity of the parallel capacitor connected to the node. For the load nodes, 012345 are used to represent the five levels of access. For node 1, 0 represents that the capacitor container is not put into use, and 12 represents other capacities connected.

[0097] (3) Elements of the augmented column

[0098] Add a column of elements to the matrix to make it an augmented matrix. The last column of elements is set to 0 or 1, where 0 represents no photovoltaic grid connection and 1 represents one photovoltaic grid connection.

[0099] 2. Algorithm solution process

[0100] 1) Initialize distribution network and algorithm related parameters;

[0101] 2) Perform genetic operations related to genetic algorithms;

[0102] 3) Calculate the fitness function value of each gene;

[0103] 4) Improve the particle swarm algorithm for calculation;

[0104] 5) Calculate the fitness function value of each particle;

[0105] 6) Determine whether the particle swarm algorithm converges. If so, go to the 7th process; if not, go to the 4th process;

[0106] 7) Determine whether the genetic algorithm has converged. If so, go to the 8th process; if not, go to the 2nd process;

[0107] 8) Output model calculation results;

[0108] 9) The model solution is completed.

[0109] Taking the 10kv distribution network as an example, the distribution network is powered by a 110kV transformer with a voltage level of 110±8×2.5% / 10.5kV. There are two groups of parallel capacitors on the 10kV bus, with compensation capacities of 2400 and 3600kvar respectively, and different distributed photovoltaics are connected to the distribution network.

[0110] (1) The optimal coding was obtained through improved genetic algorithm calculation, and the optimal way of photovoltaic access was obtained through reverse decoding. The optimal topology diagram of photovoltaic input position is as follows: Figure 3 shown.

[0111] The photovoltaic positions in the figure are optimized to be closer to the load center, thereby reducing line losses.

[0112] (2) After the improved genetic algorithm is used for calculation and before and after the optimized loss reduction strategy is implemented, the comparison between the active and reactive power output of PV1 is as follows: Figure 4 shown.

[0113] After implementing the loss reduction measures, the active output is slightly reduced and the reactive output is increased, so that the photovoltaic array outputs at maximum power near the maximum power point and the power factor approaches 1, reducing the line loss of the entire line. Figure 5 This is a comparison chart of PV1 output reactive power after implementing loss reduction measures.

[0114] (3) By implementing the loss reduction measures calculated above, the line loss rate before the implementation of the loss reduction strategy can be compared with the actual line loss rate before:

[0115] Table 1 Comparison of network loss rates before and after the implementation of optimized loss reduction measures

[0116]

[0117] The calculation results show that line losses can be reduced by optimizing the access location of distributed photovoltaics and optimizing the active and reactive output within the system to change the power factor.

[0118] The present invention comprehensively considers the impact of distributed photovoltaic grid-connected power on the network loss of the distribution network, and proposes corresponding comprehensive optimization loss reduction measures based on the actual situation of the distribution network, thereby overcoming the problem of increased network loss caused by the intermittent and fluctuating photovoltaic output power. It can promote the coordinated development of photovoltaic and distribution networks, improve the economic operation level of the distribution network, and enhance energy conservation and emission reduction of the distribution network.

Claims

1. A method for optimizing loss reduction in a distribution network containing distributed photovoltaics, characterized in that: include: Establish a two-layer loss reduction optimization model at the distribution network level and the control level; The double-layer loss reduction optimization model is solved using improved genetic algorithm and particle swarm algorithm.

2. The method for optimizing loss reduction of a distribution network containing distributed photovoltaics according to claim 1, characterized in that: The loss reduction optimization model at the distribution network level includes: Objective function: Wherein, ΔP and F represent the active power loss of the distribution network and the unit cost converted into electricity charges respectively; M, L, N represent the distribution transformer installed with parallel capacitor bank compensation, the modified line, and the collection of the modified transformer respectively, i, j, n is one of them, Q i represents the reactive power compensation capacity of the shunt capacitor on the low voltage side of the i-th distribution transformer, L j represents the length of the replaced line j, S n Indicates the capacity of the distribution transformer, f q 、f l 、f b They represent the investment cost of shunt capacitor bank compensation, and the cost of line and distribution transformer transformation respectively; Constraints: Node voltage upper and lower limit constraints IN min ≤U i ≤U max Where U i is the voltage of load node i; U max , U min are the upper and lower limits of the voltage amplitude at node i; Branch current inequality constraints I j ≤I jmax ,j=1,2,...,n n Among them, I jmax represents the maximum transmission current of line j; n n Indicates the total number of branches in the distribution network.

3. The method for optimizing loss reduction of a distribution network containing distributed photovoltaics according to claim 1 or 2, characterized in that: The loss reduction optimization model at the regulatory level includes: Objective function: f(X)=MIN∑P loss Among them, X is the set of all loss reduction measures of the control layer, expressed as [Q DG ,Q C ,D], that is, the adjustable distributed photovoltaic reactive output Q connected to the 10kV busbar of the distribution network DG , the reactive compensation capacity Q of the switchable capacitor bank C , transformer adjustable tap position D; ∑P loss It is the active power loss of the network after adopting the loss reduction measures at the distribution network control layer; Constraints: Node Voltage Constraints IN min ≤U i ≤U max Where U i is the voltage of bus node i; U max , U min is the upper and lower limits of the node voltage amplitude; Capacitor bank compensation capacity constraints Q Cmin ≤Q C ≤Q Cmax In the formula, Q Cmax It means that when all capacitor banks are put into operation, there is the maximum reactive power compensation capacity, Q Cmin Represents the constraint on the minimum compensation capacity of the capacitor bank.

4. The method for optimizing loss reduction of a distribution network containing distributed photovoltaics according to claim 1, characterized in that: The specific steps of solving the double-layer loss reduction optimization model using the improved genetic algorithm and particle swarm algorithm are as follows: Step 1: Initialize the distribution network and algorithm related parameters; Step 2: Perform relevant genetic operations of genetic algorithm; Step 3: Calculate the fitness function value of each gene; Step 4: Improve the particle swarm algorithm and calculate the fitness function value of each particle; Step 5: Determine whether the particle swarm algorithm converges, if yes, go to step 6; if no, go to step 4; Step 6: Determine whether the genetic algorithm converges, if yes, go to step 7; if no, go to step 2; Step 7: Output the model calculation results and the model solution is completed.

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