CN115940179A - Voltage collaborative loss reduction method for power distribution network comprising distributed power supply and electric automobile - Google Patents
Voltage collaborative loss reduction method for power distribution network comprising distributed power supply and electric automobile Download PDFInfo
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Abstract
The invention discloses a voltage collaborative loss reduction method for a power distribution network containing a distributed power supply and an electric automobile, which comprises the following steps: step 1, constructing a sensitivity coefficient; step 2, after a sensitivity coefficient is constructed, estimating the extreme voltage to obtain the extreme voltage and the position; step 3, after the extreme voltage and the position are obtained, performing voltage collaborative loss reduction according to the reactive power provided by the intelligent agent by adopting a reactive power control method based on the sensitivity coefficient; and 4, when the reactive power of the intelligent agent is insufficient, the expected effect cannot be achieved, and at the moment, a sensitivity-based active power reduction strategy of the distributed power supply is activated and used. The control algorithm of the present invention relies on sensitivity analysis to optimize the voltage.
Description
Technical Field
The invention relates to the technical field of energy optimization scheduling, in particular to a method for cooperatively reducing loss of voltage of a power distribution network comprising a distributed power supply and an electric automobile.
Background
The shortage of fossil energy and environmental issues are major challenges facing the world in the 21 st century, and are particularly acute for china. Diversion to electrified transportation and renewable energy sources are already in force. Based on this, massive access of distributed power supplies and electric vehicle charging stations becomes inevitable. The distributed power generation is influenced by environmental factors such as weather, seasons, geographical positions and the like, and the charging demand of the electric automobile is also influenced by user behaviors, so that uncertainty exists, and the uncertainty and randomness bring new challenges to the loss reduction of the power grid. In a traditional power distribution network, if node load is constant, and the active loss of a line is reduced, the node voltage of a balance node can only be increased, but the risk that the voltage of the balance node and the voltage of the nodes nearby the balance node is higher is caused, and the line loss and the voltage of the power distribution network need to be managed cooperatively, so that the economic stable operation of the power distribution network can be ensured.
Distributed generators based on renewable energy sources may cause overvoltage problems during peak power generation. Conversely, high penetration levels of electric vehicle charging stations increase the additional demand on the grid and may therefore cause under-voltage problems. The randomness of the charging requirements for renewable power and electric vehicles may lead to simultaneous over-voltage and under-voltage problems in multi-feed power distribution networks. This makes voltage regulation challenging and conventional voltage control devices such as on-load tap changers may suffer from rapid wear due to excessive operation.
The loss reduction strategy of a power distribution network containing a distributed power supply and an electric automobile charging pile can be researched by adopting a communication auxiliary mode, wherein the communication auxiliary mode is mainly divided into a centralized mode and a distributed mode. The traditional centralized method is characterized in that voltage coordinated loss reduction is realized, namely, a central controller is used for regulating and controlling the whole system to optimize. Distributed methods rely primarily on multi-agent systems, where all agents cooperate to reach consensus and make local decisions. The distributed approach is of increasing interest because it provides higher reliability and scalability and does not require expensive communication infrastructure. While centralized approaches are superior in performance to distributed approaches, distributed approaches can achieve satisfactory and robust results without the need to solve complex optimization algorithms.
Yan 21165bright, a reactive power optimization research on a power distribution network containing new energy and electric automobile grid connection [ J ] electric automation, 2021,43 (05): 4-6+12. But does not incorporate distributed power into voltage coordination loss reduction. J.Quiros-Tortos, L.F.Ochaa, S.W.Alnarer, et al, control of EVchargingpoints for thermal and voltage management of LVnetworks [ C ]// IEEE Trans.Power Syst., vol.31, no.4, pp.3028-3039, jul.2016. A centralized Control algorithm for electric vehicle charging was proposed to simultaneously alleviate thermal, voltage and loss problems in a power distribution network, but the voltage regulation loss reduction method herein does not coordinate a distributed power generation system with an electric vehicle. A.Nassaj and S.M.Shahrash.an.acceptable electrically controlled distributed scheme for a power distributed voltage control and reduction [ J ]. IEEE trans.Power Syst., vol.33, no.4, pp.4508-4518, jul.2018. M.C. Kisacikoglu, F.erden, and N.Erdgan.distributed control of PEV charging based on energy recovery for implementation [ J ]. IEEE trans.Info.t., vol.14, no.1, pp.332-341, jan.2018. A distributed intelligent control method for charging an electric vehicle is provided to form a charging demand curve so as to reduce the loss, but the service life of the battery is influenced due to the voltage coordinated reduction of the battery of the electric vehicle.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art, and provides a method for cooperatively controlling the voltage of a power distribution network comprising a distributed power supply and an electric automobile, so as to realize the voltage cooperative loss reduction of the power distribution network.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a voltage collaborative loss reduction method for a power distribution network comprising a distributed power supply and an electric automobile comprises the following steps:
step 1, constructing a sensitivity coefficient;
step 2, after a sensitivity coefficient is constructed, estimating the extreme voltage to obtain the extreme voltage and the position;
step 3, after the extreme voltage and the position are obtained, performing voltage collaborative loss reduction according to the reactive power provided by the intelligent agent by adopting a reactive power control method based on the sensitivity coefficient;
and 4, when the reactive power of the intelligent agent is insufficient, the expected effect cannot be achieved, and at the moment, a sensitivity-based active power reduction strategy of the distributed power supply is activated and used.
Further, the step 1 of constructing the sensitivity coefficient includes the following steps:
step 1.1, sensitivity analysis is based on a power mismatch equation at a bus i, and an expression is as follows:
in the formula, p i 、q i Respectively injecting active power and reactive power for a bus i; v i 、V j The voltage amplitude at the bus i, j is shown; b is ij 、G ij Is the real and imaginary part, δ, of the element at the ijth position ij Is the voltage angle at ij, N b The number of the buses is;
step 1.2, voltage sensitivity coefficients of active power injection and reactive power injection are expressed as follows:
in the formula (I), the compound is shown in the specification,
the effect of injecting active power on bus i on the normalized voltage change at bus j is described, and>
voltage sensitivity representing reactive power injection;
further, the step 2 of estimating the extreme voltage to obtain the extreme voltage and the position means that the extreme voltage and the position are obtained by measuring a switching value between a distributed power generation device installed at the feeder terminal and a remote terminal device by using a distributed estimation method, and includes the following steps:
step 2.1, initialization
And b i,max (0)＝b i,min (0)＝i；
Step 2.2, in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device, when the power supply is in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device
Or b i,max (k+1)≠b i,min (k) When, is greater or less>
b i,max (k+1)＝b j,max (k)；
Step 2.3, in the distributed power supply, when
And b is a i,max (k+1)＝b i,min (k) When the temperature of the water is higher than the set temperature,
b i,min (k+1)＝b j,min (k)；
step 2.4, obtaining the extreme voltage
And &>
And a position b.
Furthermore, the step 3 of performing voltage coordinated loss reduction by using the reactive power control method based on the sensitivity coefficient according to the reactive power provided by the intelligent agent refers to a reactive power control method based on a sensitivity distributed power supply and an electric vehicle charging pile, and performs voltage coordinated loss reduction by stimulating the reactive power between the distributed power supply, the electric vehicle charging pile converter and a power grid according to the sensitivity to the voltage, and includes the following steps:
step 3.1, the power distribution network optimization coordination loss reduction takes the minimum total injected reactive power as an objective function, and distribution is carried out in all intelligent agents, wherein the expression is as follows:
in the formula,. DELTA.Q i,b Incremental reactive power, omega, for agent i q All agents are intelligent agents;
step 3.2, in order to ensure that the power distribution network can safely and stably operate, the node voltage amplitude and the reactive power should meet the following constraint conditions, and the expression is as follows:
V low ≤V b ≤V up (1-5)
ΔQ i,min ≤ΔQ i,b ≤ΔQ i,max (1-6)
in the formula, V up 、V low Respectively, the upper and lower limits of the standard voltage, V b Representing the extreme voltage, Δ Q, of the network at the bus b i,max 、ΔQ i,min Respectively the upper limit and the lower limit of the reactive power of the agent i;
step 3.3, the minimum voltage deviation of reactive compensation is expressed as follows:
step 3.4, when the minimum voltage deviation is not 0, the sensitivity-based reactive power control algorithm proposed in step 3.7 is used, so equation (1-5) in step 3.2 can be substituted for the constraint, the expression is as follows:
in the formula, omega * Minimum voltage deviation of reactive compensation for target bus set
And incremental reactive power Δ Q of agent i i,b Proportioning;
step 3.5, the objective function according to step 3.1 and the constraints of step 3.4 can be re-expressed using the lagrangian function as follows, the expression:
wherein λ is q Lagrange multipliers for sensitivity-based reactive power control methods.
Step 3.6, the reactive power of the distributed power supply and the electric automobile charging pile is exchanged according to the sensitivity of the distributed power supply and the electric automobile charging pile in proportion, and the optimal increment delta Q reactive influence factor has the following expression:
in the formula (I), the compound is shown in the specification,
optimal reactive power from agent i for target bus b;
step 3.7, the reactive power control algorithm based on sensitivity can be defined as the following expression:
for
In the formula (I), the compound is shown in the specification,
representing the mismatch between the reactive power required for voltage coordination loss reduction and the total reactive power provided by the agent, N + Means that an agent sends information to other agents, and based on the information>
The ijth element, oa, of the row and column random matrix which represents the reactive power represents a sufficiently small normal number;
step 3.8, in order to satisfy the reactive power constraint in the formula (1-6) in step 3.2, a set of projection operators is defined, and the expression is as follows:
step 3.9, at the time interval t, the upper and lower limits of the increment reactive power of the agent i are expressed as follows:
ΔQ i,min ＝-ΔQ i,max (1-14)
in which the subscript t-1 denotes the fixed value in the preceding time interval, S i Indicating the rated power, P, of the agent i 、Q i Respectively representing active power and reactive power of the intelligent agent at t;
step 3.10, initializing the algorithm of formula (1-12) in step 3.8, wherein the expression is as follows:
in the formula,. DELTA.Q es,i Indicating that the total reactive power is shared between the agents on average in the initialization phase;
step 3.11, at each time interval t ∈ Ω t At the end, all variables will converge to their optimal values, as follows:
step 3.12, as the power demand changes, V g max And V g min Can naturally lie within the standard limits, i.e.
Keeping the reactive power of the agent at the value of t-1 may impose unreasonable thermal stress on the converters of the agent;
agent voltage credit C q,b In the proportion of (2), resetting the reactive power Q of the agent i,b The expression is as follows:
in the formula, C q,b Margins for the limit voltages to reach their respective limits are defined, and the expression is as follows:
further, the step 4 of activating the active power reduction strategy using the sensitivity-based distributed power supply includes the following steps:
and 4.1, activating a sensitivity-based distributed power supply active power reduction strategy if the following formula (1-19) is met:
step 4.2, estimating V g max And V g min Thereafter, the change in tap position is updated, as expressed below:
in the formula, the voltage step Δ v of each tap tr =0.0075 (per unit value);
step 4.3, the objective of the sensitivity-based active power reduction strategy of the distributed power supply is to reduce the reduction of the active power of the distributed power supply to the maximum extent, and the expression of the objective function is as follows:
4.4, based on the constraint conditions of the sensitivity-based active power reduction strategy of the distributed power supply, the expression is as follows:
V b -V min ≤V up -V low ；(1-22)
step 4.5, in order to reduce the active power of the distributed power generation device, eliminating voltage deviation for loss reduction, the expression of the voltage deviation is as follows:
in step 4.6, the formula (1-20) in step 4.2 can be replaced by the constraint condition, and the expression is as follows:
step 4.7, all the distributed power generation devices should reduce the active power according to the sensitivity in proportion, and the expression is as follows:
step 4.8, defining a reactive power reduction strategy based on sensitivity, wherein the expression is as follows:
for the
In the formula (I), the compound is shown in the specification,
is a mismatch between the power curtailment requested by the agent and the total power curtailment, <' >>
The ijth element of the random matrix of the rows and the columns representing the active power reduction;
step 4.9, because the full power of the distributed power generation is allowed to be reduced, the active power reduction strategy based on the sensitivity has no limit on the power reduction;
the distributed power generation system may reset its reduced power, the expression being as follows:
in the formula, C p,b A voltage credit for resetting the power reduction is defined, the expression being as follows:
furthermore, the extreme voltage estimation in the step 2 obtains the extreme voltage and the position without carrying out load flow calculation or measuring the voltage on each bus in the power grid.
The utility model provides a contain distributed generator and electric automobile's distribution network voltage cooperative loss reduction device, includes following module:
the step 1 comprises the following steps: a sensitivity coefficient module, whose function is to guarantee the effective cooperation of all the voltage control devices, the voltage it provides should be proportional to its sensitivity to voltage violations;
the step 2 comprises the following steps: extreme voltage estimation module, the function of which is to convert the extreme grid voltage V g max And V g min Keeping within the standard limits can ensure proper voltage regulation of the entire network;
the step 3 comprises the following steps: the reactive power control strategy module based on the sensitivity coefficient has the function of performing voltage coordination loss reduction by stimulating the reactive power between the distributed power supply and the electric automobile charging pile converter and the power grid according to the sensitivity to the voltage;
step 4 comprises the following steps: the function of the sensitivity coefficient-based active power reduction strategy module of the distributed power supply is to reduce the reduction of the active power of the distributed power supply to the maximum extent.
A computer device comprises a storage medium, a processor and a computer program which is stored on the storage medium and can run on the processor, wherein the processor executes the computer program to realize the steps of any one of the voltage collaborative loss reduction methods for the power distribution network comprising the distributed power supply and the electric automobile.
The computer storage medium stores a computer program, and the computer program is executed by a processor to implement any one of the steps of the voltage collaborative loss reduction method for the power distribution network including the distributed power supply and the electric vehicle.
Furthermore, the intelligent agent in the step 3 and the step 4 refers to a distributed power supply and an electric vehicle charging station.
Compared with the prior art, its beneficial effect lies in:
the life of the electric vehicle battery is affected because the DG and the EVCS are rarely incorporated into the grid loss reduction or the electric vehicle battery is involved in the prior art. The invention provides a distributed control algorithm, which can meet the expected charging state required by an electric automobile owner, and simultaneously schedule the residual reactive power of a DG and an EVCS (electric vehicle control system) by stimulating the reactive/active power exchange between the DG and EVCS converters and a power grid, so as to minimize the active power reduction of the DG. And the distributed power supply and the electric automobile are brought into the voltage cooperative control of the power distribution network for loss reduction.
Drawings
Fig. 1 is a power grid interface diagram of a distributed power supply and an electric vehicle charging pile provided by an embodiment of the invention;
fig. 2 is a flowchart of a voltage coordinated loss reduction method for a power distribution network including a distributed power supply and an electric vehicle according to an embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be given in order to provide those skilled in the art with a more complete, accurate and thorough understanding of the inventive concept and technical solutions of the present invention.
Example 1
As shown in fig. 2, a flow chart of a voltage collaborative loss reduction method for a power distribution network including a distributed power supply and an electric vehicle according to an embodiment of the present invention specifically includes the following steps:
step 1, constructing a sensitivity coefficient;
step 2, after a sensitivity coefficient is constructed, estimating the extreme voltage to obtain the extreme voltage and the position;
step 3, after the extreme voltage and the position are obtained, performing voltage collaborative loss reduction according to the reactive power provided by the intelligent agent by adopting a reactive power control method based on the sensitivity coefficient;
and 4, when the reactive power of the intelligent agent is insufficient, the expected effect cannot be achieved, and at the moment, a sensitivity-based active power reduction strategy of the distributed power supply is activated and used.
Example 2
The method for constructing the sensitivity coefficient in the step 1 comprises the following steps:
step 1.1, sensitivity analysis is based on a power mismatch equation at a bus i, and an expression is as follows:
in the formula, p i 、q i Respectively injecting active power and reactive power for a bus i; v i 、V j The voltage amplitudes at the buses i and j are obtained; b ij 、G ij Is the real and imaginary part, δ, of the element at the ijth position ij Is the voltage angle at ij, N b The number of the buses is;
step 1.2, voltage sensitivity coefficients of active power injection and reactive power injection are expressed as follows:
in the formula (I), the compound is shown in the specification,
the effect of injecting active power on bus i on the normalized voltage change at bus j is described, and>
voltage sensitivity representing reactive power injection;
example 3
The extreme voltage estimation to obtain the extreme voltage and the position in step 2 means that the extreme voltage and the position can be obtained by measuring a switching value between a distributed power generation device installed at a feeder terminal and a remote terminal device by using a distributed estimation method, and the method comprises the following steps:
step 2.1, initialization
And b i,max (0)＝b i,min (0)＝i；
Step 2.2, in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device, when the power supply is in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device
Or b i,max (k+1)≠b i,min (k) When, is greater or less>
b i,max (k+1)＝b j,max (k)；
Step 2.3, in the distributed power supply, when
And b is i,max (k+1)＝b i,min (k) When the temperature of the water is higher than the set temperature,
b i,min (k+1)＝b j,min (k)；
step 2.4, obtaining the extreme voltage
And &>
And a position b.
Example 4
Step 3, performing voltage collaborative loss reduction according to reactive power provided by an agent by using a sensitivity coefficient-based reactive power control method, which is a sensitivity-based reactive power control method for a distributed power supply and an electric vehicle charging pile, and performing voltage coordination loss reduction by stimulating reactive power between the distributed power supply and an electric vehicle charging pile converter and a power grid according to the sensitivity to voltage, wherein the method comprises the following steps:
step 3.1, the power distribution network optimization coordination loss reduction takes the minimum total injected reactive power as a target function, and is distributed in all intelligent agents, wherein the expression is as follows:
in the formula,. DELTA.Q i,b Incremental reactive power, Ω, for agent i q All agents are intelligent agents;
step 3.2, in order to ensure that the power distribution network can safely and stably operate, the node voltage amplitude and the reactive power should meet the following constraint conditions, and the expression is as follows:
V low ≤V b ≤V up (1-5)
ΔQ i,min ≤ΔQ i,b ≤ΔQ i,max (1-6)
in the formula, V up 、V low Respectively, the upper and lower limits of the standard voltage, V b Representing the extreme voltage, Δ Q, of the grid at the bus b i,max 、ΔQ i,min Respectively the upper limit and the lower limit of the reactive power of the agent i;
step 3.3, the minimum voltage deviation of reactive compensation is expressed as follows:
step 3.4, when the minimum voltage deviation is not 0, the sensitivity-based reactive power control algorithm proposed in step 3.7 is used, so equation (1-5) in step 3.2 can be substituted for the constraint, the expression is as follows:
in the formula, omega * Minimum voltage deviation of reactive compensation for target bus set
And incremental reactive power Δ Q of agent i i,b Proportioning;
step 3.5, the objective function according to step 3.1 and the constraints of step 3.4 can be re-expressed using the lagrangian function as follows:
wherein λ is q Lagrange multipliers for sensitivity-based reactive power control methods.
Step 3.6, the reactive power of the distributed power supply and the electric automobile charging pile should be exchanged according to the sensitivity of the distributed power supply and the electric automobile charging pile in proportion, and the optimal increment delta Q reactive influence factor is as follows:
in the formula (I), the compound is shown in the specification,
optimal reactive power from agent i for target bus b;
step 3.7, the reactive power control algorithm based on sensitivity can be defined as the following expression:
for the
/>
In the formula (I), the compound is shown in the specification,
representing the mismatch between the reactive power required for voltage coordination loss reduction and the total reactive power provided by the agent, N + Means that an agent sends information to other agents, and based on the information>
Row and column randomness for representing reactive powerThe ijth element, oa of the matrix represents a sufficiently small normal number;
step 3.8, in order to satisfy the reactive power constraint in the formula (1-6) in the step 3.2, a set of projection operators is defined, and the expression is as follows:
step 3.9, at the time interval t, the upper and lower limits of the increment reactive power of the intelligent agent i are expressed as follows:
ΔQ i,min ＝-ΔQ i,max (1-14)
in which the subscript t-1 denotes the fixed value in the preceding time interval, S i Indicating the rated power, P, of the agent i 、Q i Respectively representing active power and reactive power of the intelligent agent at t;
step 3.10, initializing the algorithm of formula (1-12) in step 3.8, wherein the expression is as follows:
in the formula,. DELTA.Q es,i Indicating that the total reactive power is shared between the agents on average in the initialization phase;
step 3.11, at each time interval t ∈ Ω t At the end, all variables will converge to their optimal values, as follows:
step 3.12, as the power demand changes, V g max And V g min Can naturally lie within standard limits, i.e.
Maintaining the reactive power of the agent at a value of t-1 may impose unreasonable thermal stress on the converters of the agent; />
Agent voltage credit C q,b Resetting the reactive power Q of the agent i,b The expression is as follows:
in the formula, C q,b Margins for the limit voltages to reach their respective limits are defined, and the expression is as follows:
example 5
Step 4, activating and using a sensitivity-based distributed power supply active power reduction strategy, comprising the following steps:
and 4.1, activating a sensitivity-based distributed power supply active power reduction strategy if the following formula (1-19) is met:
step 4.2, estimating V g max And V g min Thereafter, the change in tap position is updated, as expressed below:
in the formula, the voltage step Δ v of each tap tr =0.0075 (per unit value);
step 4.3, the objective of the sensitivity-based active power reduction strategy of the distributed power supply is to reduce the reduction of the active power of the distributed power supply to the maximum extent, and the expression of the objective function is as follows:
step 4.4, based on the constraint conditions of the active power reduction strategy of the distributed power supply with sensitivity, the expression is as follows:
V b -V min ≤V up -V low ； (1-22)
step 4.5, in order to reduce the active power of the distributed power generation device and eliminate the voltage deviation for loss reduction, the expression of the voltage deviation is as follows:
in step 4.6, the formula (1-20) in step 4.2 can be replaced by the constraint condition, and the expression is as follows:
step 4.7, all the distributed power generation devices reduce active power according to the sensitivity in proportion, and the expression is as follows:
step 4.8, defining a reactive power reduction strategy based on sensitivity, wherein the expression is as follows:
for the
/>
In the formula (I), the compound is shown in the specification,
is a mismatch between the power curtailment requested by the agent and the total power curtailment, <' >>
The ijth element of the random matrix of the rows and the columns representing the active power reduction;
step 4.9, because the full power of the distributed power generation is allowed to be reduced, the active power reduction strategy based on the sensitivity has no limit on the power reduction;
the distributed power generation system may reset its reduced power, the expression being as follows:
in the formula, C p,b A voltage credit for resetting the power reduction is defined, the expression being as follows:
example 6
The utility model provides a contain distributed generator and electric automobile's distribution network voltage cooperative loss reduction device, includes following module:
the step 1 comprises the following steps: a sensitivity coefficient module, whose function is to guarantee the effective cooperation of all the voltage control devices, the voltage it provides should be proportional to its sensitivity to voltage violations;
the step 2 comprises the following steps: extreme voltage estimation module, the function of which is to convert the extreme grid voltage V g max And V g min Keeping within the standard limits can ensure proper voltage regulation of the entire network;
the step 3 comprises the following steps: the reactive power control strategy module based on the sensitivity coefficient has the function of performing voltage coordination loss reduction by stimulating the reactive power between the distributed power supply and the electric automobile charging pile converter and the power grid according to the sensitivity to the voltage;
step 4 comprises the following steps: the function of the sensitivity coefficient-based active power reduction strategy module of the distributed power supply is to reduce the reduction of the active power of the distributed power supply to the maximum extent.
Example 7
Based on the same inventive concept, the embodiment of the present invention further provides a computer device, which includes a storage medium, a processor, and a computer program stored on the storage medium and operable on the processor, where the processor implements the steps of the method for cooperatively reducing the voltage loss of the power distribution network including the distributed power supply and the electric vehicle when executing the computer program.
Example 8
Based on the same inventive concept, the embodiment of the invention further provides a computer storage medium, wherein a computer program is stored on the computer storage medium, and when being executed by a processor, the computer program realizes the steps of the voltage collaborative loss reduction method for any power distribution network comprising the distributed power supply and the electric automobile.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (10)
1. A voltage collaborative loss reduction method for a power distribution network comprising a distributed power supply and an electric automobile is characterized by comprising the following steps:
step 1, constructing a sensitivity coefficient;
step 2, after a sensitivity coefficient is constructed, estimating the extreme voltage to obtain the extreme voltage and the position;
step 3, after the extreme voltage and the position are obtained, performing voltage collaborative loss reduction according to the reactive power provided by the intelligent agent by adopting a reactive power control method based on the sensitivity coefficient;
and 4, when the reactive power of the intelligent agent is insufficient, the expected effect cannot be achieved, and at the moment, a sensitivity-based active power reduction strategy of the distributed power supply is activated and used.
2. The voltage collaborative loss reduction method for the power distribution network comprising the distributed power supply and the electric automobile according to claim 1, wherein the step 1 of constructing the sensitivity coefficient comprises the following steps of:
step 1.1, sensitivity analysis is based on a power mismatch equation at a bus i, and an expression is as follows:
in the formula, p i 、q i Respectively injecting active power and reactive power for a bus i; v i 、V j The voltage amplitudes at the buses i and j are obtained; b is ij 、G ij Is the real and imaginary part, δ, of the element at the ijth position ij Is the voltage angle at ij, N b The number of the buses is;
step 1.2, voltage sensitivity coefficients of active power injection and reactive power injection are expressed as follows:
in the formula (I), the compound is shown in the specification,
the effect of injecting active power on bus i on the normalized voltage change at bus j is described, and>
indicating the voltage sensitivity of the reactive power injection.
3. The voltage collaborative loss reduction method for the power distribution network comprising the distributed power supply and the electric automobile according to claim 1, wherein the step 2 of estimating the extreme voltage to obtain the extreme voltage and the position means that the extreme voltage and the position are obtained by measuring a switching value between a distributed power generation device installed at a feeder terminal and a remote terminal device by using a distributed estimation method, and the method comprises the following steps:
step 2.1, initialization
And b i,max (0)＝b i,min (0)＝i；
Step 2.2, in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device, when the power supply is in the distributed power supply, the electric automobile charging pile, the on-load tap-changer and the remote terminal device
Or b i，max (k+1)≠b i，min (k) In combination of time>
b i,max (k+1)＝b j,max (k)；
Step 2.3, in the distributed power supply, when
And b is a i,max (k+1)＝b i,min (k) When, is greater or less>
b i,min (k+1)＝b j,min (k)；
Step 2.4, obtaining the extreme voltage
And &>
And a position b.
4. The voltage coordinated loss reduction method of the power distribution network comprising the distributed power supply and the electric automobile according to claim 1, wherein the step 3 of performing voltage coordinated loss reduction according to the reactive power provided by the intelligent agent by using the reactive power control method based on the sensitivity coefficient is a reactive power control method of the distributed power supply and the electric automobile charging pile based on the sensitivity, and the method performs voltage coordinated loss reduction by stimulating the reactive power between the distributed power supply and the electric automobile charging pile and the power grid according to the sensitivity to the voltage, and comprises the following steps:
step 3.1, the power distribution network optimization coordination loss reduction takes the minimum total injected reactive power as an objective function, and distribution is carried out in all intelligent agents, wherein the expression is as follows:
in the formula,. DELTA.Q i,b Incremental reactive power, omega, for agent i q All agents are intelligent agents;
3.2, in order to ensure that the power distribution network can safely and stably operate, the node voltage amplitude and the reactive power meet the following constraint conditions, wherein the expression is as follows:
V low ≤V b ≤V up (1-5)
ΔQ i,min ≤ΔQ i,b ≤ΔQ i,max (1-6)
in the formula, V up 、V low Respectively, the upper and lower limits of the standard voltage, V b Representing the extreme voltage of the grid at the bus b, Δ Q i,max 、ΔQ i,min respectively the upper limit and the lower limit of the reactive power of the agent i;
step 3.3, the minimum voltage deviation of reactive compensation is expressed as follows:
step 3.4, when the minimum voltage deviation is not 0, the sensitivity-based reactive power control algorithm proposed in step 3.7 is used, so equation (1-5) in step 3.2 can be substituted as a constraint, the expression is as follows:
in the formula, omega * For the target bus set, the minimum voltage deviation DeltaV of reactive compensation b Q And incremental reactive power Δ Q of agent i i,b Proportionally mixing;
step 3.5, the objective function according to step 3.1 and the constraints of step 3.4 can be re-expressed using the lagrangian function as follows, the expression:
wherein λ is q Lagrangian multipliers for sensitivity-based reactive power control methods;
step 3.6, the reactive power of the distributed power supply and the electric automobile charging pile is exchanged according to the sensitivity of the distributed power supply and the electric automobile charging pile in proportion, and the optimal increment delta Q reactive influence factor has the following expression:
in the formula (I), the compound is shown in the specification,
optimal reactive power from agent i for target bus b；
Step 3.7, the sensitivity-based reactive power control algorithm can be defined as the following expression:
for the
In the formula (I), the compound is shown in the specification,
representing the mismatch between the reactive power required for voltage coordination loss reduction and the total reactive power provided by the agent, N + Indicating that an agent is sending information to another agent, based on the status of the agent>
The ijth element, oa, of the row and column random matrix which represents the reactive power represents a sufficiently small normal number;
step 3.8, in order to satisfy the reactive power constraint in the formula (1-6) in the step 3.2, a set of projection operators is defined, and the expression is as follows:
step 3.9, at the time interval t, the upper and lower limits of the increment reactive power of the agent i are expressed as follows:
ΔQ i,min ＝-ΔQ i,max (1-14)
in which the subscript t-1 denotes the fixed value in the preceding time interval, S i Indicating the rated power, P, of the agent i 、Q i Respectively representing active power and reactive power of the intelligent agent at t;
step 3.10, initializing the algorithm of formula (1-12) in step 3.8, wherein the expression is as follows:
ΔQ i,b (0)＝0
in the formula,. DELTA.Q es,i Indicating that the total reactive power is shared between the agents on average in the initialization phase;
step 3.11, at each time interval t e Ω t At the end, all variables will converge to their optimal values, as follows:
when in use
Step 3.12, as the power demand changes, V g max And V g min Can naturally lie within the standard limits, i.e.
General intelligenceKeeping the reactive power of the agent at the value of t-1 may impose unreasonable thermal stresses on the converters of the agent;
agent voltage credit C q,b In the proportion of (2), resetting the reactive power Q of the agent i,b The expression is as follows:
in the formula, C q,b Margins for the limit voltages to reach their respective limits are defined, and the expression is as follows:
5. the method for cooperatively reducing the voltage of the power distribution network comprising the distributed power supply and the electric automobile according to claim 1, wherein the step 4 of activating the sensitivity-based distributed power supply active power reduction strategy comprises the following steps:
and 4.1, activating a sensitivity-based distributed power supply active power reduction strategy if the following formula (1-19) is met:
step 4.2, estimating V g max And V g min Thereafter, the change in tap position is updated, as expressed below:
in the formula, the voltage step Δ v of each tap tr =0.0075 (per unit value);
step 4.3, the objective of the sensitivity-based active power reduction strategy of the distributed power supply is to reduce the reduction of the active power of the distributed power supply to the maximum extent, and the expression of the objective function is as follows:
4.4, based on the constraint conditions of the sensitivity-based active power reduction strategy of the distributed power supply, the expression is as follows:
V b -V min ≤V up -V low ； (1-22)
step 4.5, in order to reduce the active power of the distributed power generation device, eliminating voltage deviation for loss reduction, the expression of the voltage deviation is as follows:
in step 4.6, the formula (1-20) in step 4.2 can be replaced by the constraint condition, and the expression is as follows:
step 4.7, all the distributed power generation devices should reduce the active power according to the sensitivity in proportion, and the expression is as follows:
step 4.8, reactive power reduction strategy definition based on sensitivity, wherein the expression is as follows:
for the
In the formula (I), the compound is shown in the specification,
is a mismatch between the power curtailment requested by the agent and the total power curtailment, <' >>
The ijth element of the random matrix of the rows and the columns representing the active power reduction;
step 4.9, because the full power of the distributed power generation is allowed to be reduced, the active power reduction strategy based on the sensitivity has no limit on the power reduction;
the distributed power generation system may reset its reduced power, expressed as follows:
in the formula, C p,b A voltage credit for resetting the power reduction is defined, the expression being as follows:
6. the voltage collaborative loss reduction method for the power distribution network comprising the distributed power supply and the electric automobile according to claim 1, wherein the extreme voltage estimation in the step 2 is used for obtaining the extreme voltage and the position without carrying out load flow calculation or measuring the voltage on each bus in the power grid.
7. The utility model provides a contain distributed generator and electric automobile's distribution network voltage and fall in coordination and lose device which characterized in that includes following module:
a sensitivity coefficient module, whose function is to guarantee the effective cooperation of all the voltage control devices, the voltage it provides should be proportional to its sensitivity to voltage violations;
extreme voltage estimation module, the function of which is to convert the extreme grid voltage V g max And V g min Keeping within the standard limits can ensure proper voltage regulation of the entire network;
the reactive power control strategy module based on the sensitivity coefficient has the function of performing voltage coordination loss reduction by stimulating reactive power between the distributed power supply and the electric vehicle charging pile converter and the power grid according to the sensitivity to voltage;
the distributed power supply active power reduction strategy module based on the sensitivity coefficient has the function of reducing the reduction of the distributed power supply active power to the maximum extent.
8. A computer device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein: the processor executes the computer program to realize the steps of any one of the methods for cooperatively reducing the voltage of the power distribution network comprising the distributed power supply and the electric automobile, which are disclosed in claims 1 to 6.
9. A computer storage medium, wherein a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the computer program implements the steps of the method for cooperatively reducing the voltage drop of the power distribution network including the distributed power supply and the electric vehicle according to any one of claims 1 to 6.
10. The method for the coordinated voltage loss reduction of the power distribution network comprising the distributed power sources and the electric vehicles according to claim 1, wherein the agents in the step 3 and the step 4 refer to the distributed power sources and the electric vehicle charging stations.
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