CN116191575B - Operation control method and system for participation of optical storage system in power grid voltage regulation auxiliary service - Google Patents
Operation control method and system for participation of optical storage system in power grid voltage regulation auxiliary service Download PDFInfo
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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Abstract
The invention discloses an operation control method and an operation control system for an optical storage system participating in power grid voltage regulation auxiliary service, and belongs to the field of new energy and electric power. Comprising the following steps: an interactive optimization model of the optical storage system participating in auxiliary service of the active power distribution network is established, and a distributed optimization solving method based on the model is provided based on a distributed alternating direction multiplier algorithm. The method can realize that the optical storage system with the multi-decision main body attribute of target conflict is connected into the power grid and participates in the power grid voltage regulation auxiliary service in a deep level, and meanwhile, the provided distributed optimization solving method can effectively solve the problems of high dimensionality and difficult solving of the interactive optimization model, and avoids the risks of complete data information, privacy leakage and the like in the traditional centralized optimization algorithm; in addition, the method provided by the invention can effectively mobilize the reactive-voltage and active-power supporting potential of the optical storage system, reduce the running loss of the power grid, improve the voltage running safety of the power grid and realize the goal agreement of the power grid and the optical storage system.
Description
Technical Field
The invention belongs to the field of new energy and electric power, and particularly relates to an operation control method and system for a light storage system to participate in power grid voltage regulation auxiliary service.
Background
With the rapid and rapid development of renewable energy sources such as distributed photovoltaic and the like and high penetration access of the renewable energy sources in a power grid, the inherent randomness and fluctuation of the renewable energy sources also bring serious risks and challenges to the power quality and the safety of the power grid. The construction of energy storage resources and the development of a more flexible optical storage system are powerful means for coping with the problems of randomness and fluctuation of the distributed photovoltaic output power, but the development of the optical storage system still faces the dilemma that the construction consumption resources are high, the safety problem is complex and the like at the present stage, so that the construction utilization efficiency of the optical storage system is still low, the growth speed and the growth scale are still limited, and therefore, how to improve the operation benefit of the optical storage system becomes a key problem to be solved urgently.
At present, aiming at the research and development of the value-added synergy of an optical storage system by participating in the interactive operation of a power grid, for example, (1) an evaluation system of the system is established through annual load electricity deficiency rate, energy wave rate, energy fluctuation rate and comprehensive consumption resource, and finally the annual load electricity deficiency rate is used as a constraint condition and the quantity constraint of each power generation unit is added, and the system is subjected to multi-objective optimization solution by a method combining a genetic algorithm and a weight coefficient change method, so that the optimal system configuration and operation scheme are obtained; (2) Taking the wind and light discarding penalty into consideration, consuming resources, establishing a day-ahead optimal scheduling model of the wind and light storage hydrogen production system, and optimally solving the optimal scheduling model by adopting a self-adaptive simulated annealing particle swarm algorithm; (3) The method comprises the steps of taking the minimum load variance at the power grid side, the minimum operation and maintenance consumption resource of an energy storage system and the minimum electricity purchasing cost to the power grid as objective functions, taking the power of the energy storage system, the state of charge and the power of the power grid side as constraint conditions, establishing a multi-objective optimization operation model of the energy storage system, and solving by adopting an NSGA-III algorithm to obtain a Pareto optimal solution set.
However, most of the optical storage systems researched by the method pay attention to the running of the power grid, the optical storage systems with multi-decision main attribute and the power grid are in interactive running, and in addition, the interactive running of the optical storage systems and the power grid is mostly focused on the problem of interactive running optimization in a fixed power environment in a power control mode, but the research on the deep participation of the optical storage systems in the interaction of power auxiliary services, especially the participation of the voltage control auxiliary services, is very involved, and the optical storage systems actually have better reactive-voltage and active-power supporting capability, so that the potential of the optical storage systems in the power grid voltage control auxiliary services needs to be further explored, the corresponding interactive optimization mode is explored, and the aim of the optical storage systems and the power grid under the multi-decision main attribute is achieved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide the operation control method and the system for the participation of the optical storage system in the power grid voltage regulation auxiliary service, and aims to solve the problems of high dimensionality and difficult solution of an interactive optimization model and avoid the risks of complete data information, privacy leakage and the like in the traditional centralized optimization algorithm.
In order to achieve the above object, in a first aspect, the present invention provides an operation control method for a light storage system participating in a grid voltage regulation auxiliary service, where the light storage system has a multi-decision main attribute of target conflict, the method includes:
s1, constructing an integral operation control model of the light storage system participating in power grid voltage regulation auxiliary service, wherein the integral operation control model comprises the following steps: the power grid side operation control model and the optical storage system operation control model; wherein,
the grid-side operation control model includes: the decision variable is expected operation power sent by the power grid to the optical storage system in each time period, the optimization target is to minimize operation consumption resources, the operation consumption resources consist of network damage consumption resources, auxiliary service consumption resources and power grid voltage out-of-limit cost, and the operation constraint comprises power grid node voltage constraint, power grid branch transmission power constraint and network power flow constraint;
the optical storage system operation control model comprises: the decision variable is the operation power of each optical storage system in each time period for responding to auxiliary service, the optimization target is the maximization of operation benefit, the operation benefit is composed of the consumption of resources of life loss and the participation of the optical storage system in the harvest of the auxiliary service, and the operation constraint comprises the charge and discharge power constraint of the energy storage equipment and the operation constraint of the energy storage SOC;
s2, carrying out augmented Lagrangian equivalent transformation on the integral operation control model by introducing Lagrangian multipliers, penalty coefficients and auxiliary variables to obtain a distributed optimization equivalent model of the power grid and each optical storage system;
s3, carrying out distributed alternate iterative solution on the power grid and the distributed optimization equivalent model of each optical storage system by adopting an alternate direction multiplier method, and obtaining the optimal interactive operation power of the optical storage system participating in the voltage regulation auxiliary service of the power grid.
Preferably, the objective function of the grid-side operation control model is specifically as follows:
wherein ,Xnet For controlling a variable X of a power grid side operation control model net ＝[X net (1),...,X net (t),...]，X net (t) is a vector formed by expected active power and reactive power emitted by the power grid to the optical storage system in the t time period, C DN C, running total consumption resources for the power grid loss Consuming resources for network damages of the power grid, C bat Invoking consumed resources of the optical storage system on auxiliary service for the power grid, C pen The voltage out-of-limit cost of the power grid node is calculated; t is the total time period number of the optimized operation control, P loss (t) is the total loss power of the power grid in the period of t, c t For the consumption item of t time period units, M is the number of the optical storage system, M is the set formed by all the optical storage systems, and P net,m (t),Q net,m (t) respectively expecting active power and reactive compensation power of the mth optical storage system in t time period for the power grid, wherein deltat is the unit time length, c bat (t) is a unit consumption term of the optical storage system in a t time period, and omega is a distribution proportionality coefficient of the unit consumption term of the optical storage system on active and reactive power;respectively crossing upper limit parameters and lower limit parameters of voltage of all voltage nodes of the power grid in a t time period; lambda (lambda) pen And the grid cost coefficient is obtained after the voltage is out of limit.
Preferably, the operation constraint of the grid-side operation control model is specifically as follows:
P i min ≤P i (t)≤P i max
Q i min ≤Q i (t)≤Q i max
wherein ,respectively crossing upper limit parameters and lower limit parameters of voltage of all voltage nodes of the power grid in a t time period, wherein i is the number of the nodes of the power grid, omega is a set formed by the numbers of all the nodes of the power grid, and U is a set of the numbers of the nodes of the power grid max ,U min Respectively the maximum value and the minimum value of the node voltage, U i (t) is the voltage of node i in time period t, P i (t),Q i (t) active power and reactive power limits of the grid node i in the t period, respectively,/->Minimum active power and maximum active power of node i, respectively, +.>Minimum reactive power and maximum reactive power of node i, P j ,Q j Active and reactive power, P, flowing respectively from node j to the node below ij ,Q ij Active power and reactive power flowing to a node j of the power grid node i respectively; r is (r) ij ,x ij Resistance and reactance between node i and node j, respectively, +.>Active and reactive power of the load of node j, respectively,/->Distributed photovoltaic output of node j, < >>The active power and the reactive power of the optical storage system which are respectively called by the power grid to the node j are I as an absolute value operator.
Preferably, the objective function of the optical storage system operation control model is specifically as follows:
wherein ,Xm Optimizing control model control variables X for optical storage system m ＝[X m (1),...,X m (T)]，X m (T) is a vector formed by active power and reactive power which are transmitted by the mth optical storage system to auxiliary service and are meant to participate, T is the total time period number of the optimal operation control,harvesting of the mth optical storage system participating in grid auxiliary service, P m (t),Q m (t) respectively responding the active electric power and the reactive compensation power of the auxiliary service in the t time period for the mth optical storage system, c c Resource coefficients are consumed for the unit electric quantity of the optical storage system; Δt is the time interval, || is the absolute value operator.
Preferably, the operation constraint of the optical storage system operation control model is specifically as follows:
wherein ,Pm (t),Q m (t) respectively responding the active electric power and reactive compensation power of the auxiliary service in the t time period for the mth optical storage system,reactive compensation power minimum and maximum values for the mth optical storage system in response to the auxiliary service in the t period,/for the mth optical storage system>Respectively the discharge power and the charge power of the energy storage in the mth optical storage system in the t time period,respectively, the maximum discharge power and the maximum charge power allowed by energy storage in the mth optical storage system, < +.>For the charge state of energy stored in the mth optical storage system in the t time period, E bat,m Is the maximum capacity of energy storage in the mth optical storage system, delta t is the time interval, eta c,m ,η d,m Respectively the charging and discharging efficiency of the energy storage in the mth optical storage system,/for>Maximum and minimum constraints of the state of charge of the stored energy in the mth optical storage system, respectively,/->The initial charge state and the final charge state of the energy storage in the operation control in the mth optical storage system are respectively.
Preferably, step S2 includes:
s21, introducing Lagrangian multipliersAnd penalty coefficient ρ, equivalent the grid-side operation control model to an augmented lagrangian optimization objective function form:
s22, introducing Lagrangian multipliersAnd penalty coefficient ρ, equivalent the optical storage system operation control model to an augmented lagrangian optimization objective function form:
s23, will and />Unifying the obtained values to be Z, and constructing an extended Lagrangian function of the auxiliary variable Z:
wherein ,Xnet For controlling a variable X of a power grid side operation control model net ＝[X net (1),...,X net (t),...]，X net (t)＝[P net,1 (t),...,P net,m (t),Q net,1 (t),...,Q net,m (t)]，P net,m (t),Q net,m (t) respectively obtaining active power and reactive compensation power of the power grid expected optical storage system m in t time period, C DN (X net ) The total consumption of resources for the operation of the power grid,the Lagrangian multiplier corresponding to the kth iterative process after the equivalent conversion of the power grid operation control model is adopted, ρ is a punishment coefficient, T is an optimization time period number, T is an optimization operation control total time period number, and>the method comprises the steps that the method is an auxiliary variable corresponding to a kth iterative process after the power grid operation control model is equivalently converted, and the I is a two-norm operator; x is X m Controlling a model control variable X for the operation of the optical storage system m ＝[X m (1),...,X m (T)]，X m (t)＝[P m (t),Q m (t)]，P m (t),Q m (t) the intended active power and reactive compensation power respectively transmitted by the optical storage system m to the auxiliary service in the t period,/>Harvesting of the mth optical storage system involved in the grid auxiliary service,/->Equivalent transformation for control model of optical storage systemLagrangian multiplier corresponding to the k-th iteration process, and +.>The auxiliary variable corresponding to the kth iteration process after the equivalent transformation of the optical storage system operation control model is adopted; z is Z k Is an auxiliary variable +.> and />The unified set X is the control variable X of the operation control model of the optical storage system m And grid optimization control model control variable X net Lambda of (x) k As auxiliary variable Z k The Lagrangian multiplier corresponding to the kth iterative updating process.
Preferably, step S3 includes:
s31, setting maximum iteration times and convergence accuracy, and setting upper and lower limits of unit consumption items between the optical storage system and the power gridInitializing a unit compensation item of a power grid to a light storage system to be 0, initializing iteration number k to be 0 and initializing independent variablesInitializing auxiliary variable +.>Initializing the augmented lagrangian multiplier +.>And penalty coefficient ρ 0 Wherein T e [1,2, ], t.]，m∈M；
S32, for the main body of the power grid, receiving the active power expected to be distributed to auxiliary services of the power grid from each optical storage systemAnd reactive power->According to the augmentation Lagrangian optimization objective function and the operation constraint of the power grid side operation control model and the like, solving the distributed optimization model to obtain active power +.>And reactive power
S33, for each optical storage system, receiving the expected active power of the optical storage system from the power gridAnd reactive power->According to the operational control model of the optical storage system, the Lagrangian optimization objective function and operational constraint are enhanced, the distributed optimization model is solved, and the output quantity of the optical storage system m responding to the auxiliary service of the power grid is obtained>And reactive compensation quantity->
S34, updating active power reference values of main bodies of all optical storage system power stations in response to auxiliary services of active power distribution networkAnd reactive power reference value->Auxiliary variable->
S35, updating Lagrangian multiplierPenalty coefficient ρ k+1 Update iteration number k=k+1:
wherein ,for self-disability, add->Is the mutual residual error;
s36, calculating the total power of the optical storage system participating in auxiliary serviceCalculating unit compensation term of optical storage system
Where α is the attenuation coefficient.
S37, judging whether iteration termination conditions are met according to the mutual residual errors and the self-residual errors of the variables, if yes, ending, otherwise, returning to the step S32.
In order to achieve the above object, in a second aspect, the present invention provides an operation control system for a light storage system participating in a voltage regulation auxiliary service of a power grid, including: a processor and a memory; the memory is used for storing computer execution instructions; the processor is configured to execute the computer-executable instructions such that the method of the first aspect is performed.
In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:
the invention provides an operation control method and system for an optical storage system to participate in power grid voltage regulation auxiliary service, comprising the following steps: an interactive optimization model of the optical storage system participating in auxiliary service of the active power distribution network is established, and a distributed optimization solving method based on the model is provided based on a distributed alternating direction multiplier algorithm. The method can realize that the optical storage system with the multi-decision main body attribute of target conflict is connected into the power grid and participates in the power grid voltage regulation auxiliary service in a deep level, and meanwhile, the provided distributed optimization solving method can effectively solve the problems of high dimensionality and difficult solving of the interactive optimization model, and avoids the risks of complete data information, privacy leakage and the like in the traditional centralized optimization algorithm; in addition, the method provided by the invention can effectively mobilize the reactive-voltage and active-power supporting potential of the optical storage system, reduce the running loss of the power grid, improve the voltage running safety of the power grid and realize the goal agreement of the power grid and the optical storage system.
Drawings
Fig. 1 is a flowchart of an operation control method for a light storage system participating in a voltage regulation auxiliary service of a power grid.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the invention provides an operation control method for a light storage system to participate in a voltage regulation auxiliary service of a power grid, comprising the following steps:
step 1, an operation control model of the optical storage system participating in the power grid voltage regulation auxiliary service is built, wherein the operation control model comprises an operation control model of a power grid side and an operation control model of the optical storage system.
1) The method comprises the steps of constructing a grid side optimization control model, wherein an optimization operation target is to minimize operation consumption resources, the optimization operation target mainly comprises network damage consumption resources, auxiliary service consumption resources and grid voltage out-of-limit cost, and operation constraints comprise grid node voltage constraints, grid branch transmission power constraints, network power flow constraints and the like. The operation optimization objective of the constructed grid-side control model is as follows:
wherein ,Xnet Optimizing control variables of a control model for a power grid, expressed as X m ＝[X m (1),...,X m (T)]，C DN C, running total consumption resources for the power grid loss Consuming resources for network damages of the power grid, C bat Invoking consumed resources of the optical storage system on auxiliary service for the power grid, C pen The voltage out-of-limit cost of the power grid node is calculated; t is the total time period number of the optimized operation control, and the invention adopts 24 hours and P loss (t) is the total loss power of the power grid in the period of t, c t Expending items for t time period units, P net,m (t)，Q net,m (t) respectively obtaining active power and reactive compensation power of a power grid expected light storage system M in a t time period, wherein M is the number of the light storage system, M is a set formed by a plurality of light storage systems, deltat is the unit time length, and c bat (t) is a unit consumption term of the optical storage system in a t time period, and omega is a distribution proportionality coefficient of the unit consumption term of the optical storage system on active and reactive power;respectively crossing upper limit parameters and lower limit parameters of voltage of all voltage nodes of the power grid in a t time period, wherein i is the number of the nodes of the power grid, omega is the set formed by the numbers of all the nodes of the power grid, and when ∈ ->Node voltage out-of-limit is represented in time 1, and all nodes of the power grid meet safety constraint when the node voltage out-of-limit is 0; lambda (lambda) pen U is the cost coefficient of the power grid after the voltage is out of limit max ,U min Respectively the maximum value and the minimum value of the node voltage, U i And (t) is the voltage of node i in the t period.
The power flow constraint and the power limit constraint met by the power grid are as follows:
P i min ≤P i (t)≤P i max (6)
Q i min ≤Q i (t)≤Q i max (7)
wherein ,Pi (t)，Q i (t) active power and reactive power limits of the grid node i in the t time period respectively,minimum active power and maximum active power of node i, respectively, +.>Minimum reactive power and maximum reactive power of node i, P ij ，Q ij Active and reactive power respectively flowing to node j for grid node i, P j ，Q j Active power and reactive power respectively flowing to a lower node for the node j; r is (r) ij ,x ij The resistance and reactance between node i and node j respectively,active and reactive power of the load of node j, respectively,/->The distributed photovoltaic output of node j,and respectively calling active power and reactive power of the optical storage system to the node j for the power grid.
2) An optical storage system operation optimization control model is built, an optimization operation target is to maximize operation benefit, the optimization target comprises life loss consumption resources and harvest of auxiliary services of the optical storage system, and operation constraints comprise charge and discharge power constraint of energy storage equipment, energy storage SOC operation constraint and the like. Wherein the optimization objective function is expressed as follows:
wherein ,Xm Optimizing control model control variable for optical storage system expressed as X m ＝[X m (1),...,X m (T)]，Harvesting of the mth optical storage system participating in grid auxiliary service, P m (t)，Q m (t) respectively responding the active electric power and the reactive compensation power of the auxiliary service in the t time period for the mth optical storage system, c c Resource coefficients are consumed for the unit electric quantity of the optical storage system; Δt is the time interval, ||is the absolute value operator, and the number M epsilon M of the optical storage system.
The following constraints are satisfied for the operation of the optical storage system:
P m (t)＝P dis,m (t)-P ch,m (t) (12)
wherein ,respectively the discharge power and the charge power of the energy storage in the mth optical storage system in the t time period,respectively, the maximum discharge power and the maximum charge power allowed by energy storage in the mth optical storage system, < +.>For the state-of-charge (SOC) of energy storage in the mth optical storage system in the t period, E bat,m Is the maximum capacity of energy storage in the mth optical storage system, delta t is the time interval, eta c,m ，η d,m Respectively the charging and discharging efficiency of the energy storage in the mth optical storage system,/for>Maximum and minimum constraints of the state of charge of the stored energy in the mth optical storage system, respectively,/->The initial charge state and the final charge state of the energy storage in the operation control in the mth optical storage system are respectively. The essence of constraint (14): the energy storage is in the constraint of charging and discharging states, when the charging power is greater than 0, the discharging power is 0; conversely, when the discharge power is greater than 0, the charge power must be 0.
And step 2, introducing Lagrange multipliers, penalty coefficients and auxiliary variables, and performing augmentation Lagrange equivalent transformation on the model constructed in the step 1 to obtain a distributed optimization equivalent model of the power grid and each optical storage system.
1) For the constructed grid side optimization control model, lagrange multiplier lambda is introduced k And a penalty coefficient rho, the grid side optimization control model is transformed into an amplified Lagrange optimization objective function form, and the amplified objective function is shown as a formula (18):
wherein ,Xnet Optimizing control variables of a control model for a power grid, expressed as X net ＝[X net (1),...,X net (t),...]Refers to the expected active power and reactive power emitted by the power grid to the optical storage system, wherein X net (t)＝[P net,1 (t),...,P net,m (t),Q net,1 (t),...,Q net,m (t)]，P net,m (t)，Q net,m (t) respectively obtaining active power and reactive compensation power of the power grid expected optical storage system m in t time period, C DN (X net ) The total consumption of resources for the operation of the power grid,the Lagrangian multiplier corresponding to the kth iterative process after the equivalent conversion of the power grid operation control model is adopted, ρ is a punishment coefficient, T is an optimization time period number, T is an optimization operation control total time period number, and>and (3) for auxiliary variables corresponding to the kth iterative process after the equivalent transformation of the power grid operation control model, the operation constraint to be met by the power grid operation control model after the equivalent transformation is shown in formulas (6) - (9), and the I is a two-norm operator.
2) Introducing a distributed extended Lagrange function of each optical storage system to the constructed optical storage system optimization control model to obtain an extended Lagrange optimization objective function of each optical storage system, wherein the extended Lagrange optimization objective function is shown as a formula (19):
wherein ,Xm Optimizing control model control variable for optical storage system expressed as X m ＝[X m (1),...,X m (T)]Including active and reactive power, X, of intended participation by the optical storage system in the auxiliary service m (t)＝[P m (t),Q m (t)]，P m (t)，Q m (t) the intended active power and reactive compensation power respectively transmitted by the optical storage system m to the auxiliary service in the t period,harvesting of the mth optical storage system involved in the grid auxiliary service,/->Lagrangian multiplier corresponding to the kth iterative process after equivalent transformation of the optimal control model of the optical storage system, ρ is a penalty coefficient, T is an optimal time period number, T is an optimal operation control total time period number, and->For auxiliary variables corresponding to the kth iterative process after the equivalent transformation of the optimal control model of the optical storage system, the operation constraint which needs to be met by the optimal control model of the optical storage system is shown in formulas (11) - (17).
3) For introduced auxiliary variables and />Unifying the two values as Z, and constructing an extended Lagrangian function of an auxiliary variable Z as shown in a formula (20):
wherein ,Zk As an auxiliary variable and />Unified set, X is the control variable X of the optimal control model of the optical storage system m And grid optimization control model control variable X net Is set of (1)Lambda of the combination k As auxiliary variable Z k Lagrangian multiplier corresponding to the kth iterative updating process, ρ is a penalty coefficient, T is an optimization time period number, and T is an optimization operation control total time period number.
And 3, carrying out distributed alternate iterative solution on the distributed optimization equivalent model based on the augmented Lagrangian function constructed in the step 2 by adopting an alternate direction multiplier method, and obtaining the optimal interactive operation power of the optical storage system participating in the grid voltage regulation auxiliary service.
1) Setting the maximum iteration number k max Convergence accuracy xi, setting upper and lower limits of unit consumption items between optical storage system and power gridInitializing a unit compensation item of a power grid to a light storage system to be 0, initializing iteration number k to be 0 and initializing independent variablesInitializing auxiliary variable +.>Initializing the augmented lagrangian multiplier +.>And penalty coefficient ρ 0 Wherein T e [1,2, ], t.]，m∈M；
2) For the main body of the power grid, the active power which is expected to be distributed to auxiliary services of the power grid is received from each optical storage systemAnd reactive power->Solving a distributed optimization model according to a formula (18) and a constraint thereof to obtain active power +.>And reactive power->
3) For optical storage system i, receiving an electrical grid desired optical storage system active power from an electrical gridAnd reactive powerSolving a distributed optimization model according to a formula (19) and a constraint thereof to obtain the output quantity of the light storage system i responding to the auxiliary service of the power grid +.>And reactive compensation quantity->
4) Updating the active power of each optical storage system power station main body in response to the auxiliary service of the active power distribution network according to a formula (21)And reactive power->Reference value, update auxiliary variable ++according to equation (22)>
5) Updating Lagrangian multiplier according to equation (23)Calculating mutual residual error and self residual error of variables according to formula (24), and updating penalty coefficient rho according to formula (25) k Updating the iteration number k=k+1;
wherein ,for self-disability, add->Is the mutual residual.
6) Calculating the total power of the optical storage system participating in auxiliary service according to a formula (26), and calculating and updating the unit compensation term of the optical storage system according to a formula (27)
Where α is the attenuation coefficient.
7) And (3) calculating the mutual residual error and the self-residual error of the variables according to the formula (24), judging the convergence condition of the algorithm, if the iteration termination condition shown in the formula (28) is met, exiting the loop, otherwise returning to the flow 2), and stopping until the convergence condition is met or the maximum iteration times are reached.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. An operation control method for a light storage system to participate in power grid voltage regulation auxiliary service is characterized in that the light storage system has a multi-decision main attribute of target conflict, and the method comprises the following steps:
s1, constructing an integral operation control model of the light storage system participating in power grid voltage regulation auxiliary service, wherein the integral operation control model comprises the following steps: the power grid side operation control model and the optical storage system operation control model; wherein,
the grid-side operation control model includes: the decision variable is expected operation power sent by the power grid to the optical storage system in each time period, the optimization target is to minimize operation consumption resources, the operation consumption resources consist of network damage consumption resources, auxiliary service consumption resources and power grid voltage out-of-limit cost, and the operation constraint comprises power grid node voltage constraint, power grid branch transmission power constraint and network power flow constraint;
the optical storage system operation control model comprises: the decision variable is the operation power of each optical storage system in each time period for responding to auxiliary service, the optimization target is the maximization of operation benefit, the operation benefit is composed of the consumption of resources of life loss and the participation of the optical storage system in the harvest of the auxiliary service, and the operation constraint comprises the charge and discharge power constraint of the energy storage equipment and the operation constraint of the energy storage SOC;
s2, carrying out augmented Lagrangian equivalent transformation on the integral operation control model by introducing Lagrangian multipliers, penalty coefficients and auxiliary variables to obtain a distributed optimization equivalent model of the power grid and each optical storage system;
s3, carrying out distributed alternate iterative solution on the power grid and the distributed optimization equivalent model of each optical storage system by adopting an alternate direction multiplier method to obtain the optimal interactive operation power of the optical storage system participating in the voltage regulation auxiliary service of the power grid;
the step S2 comprises the following steps:
s21, introducing Lagrangian multipliersAnd penalty coefficient ρ, equivalent the grid-side operation control model to an augmented lagrangian optimization objective function form:
s22, introducing Lagrangian multipliersAnd penalty coefficient ρ, equivalent the optical storage system operation control model to an augmented lagrangian optimization objective function form:
s23, will and />Unifying the obtained values to be Z, and constructing an extended Lagrangian function of the auxiliary variable Z:
wherein ,Xnet For controlling a variable X of a power grid side operation control model net ＝[X net (1),...,X net (t),...]，X net (t) is a vector formed by expected active power and reactive power emitted by the power grid to the optical storage system in the t time period, and X net (t)＝[P net,1 (t),...,P net,m (t),Q net,1 (t),...,Q net,m (t)]，P net,m (t),Q net,m (t) respectively obtaining active power and reactive compensation power of a power grid expected optical storage system m in a t time period, wherein m is the number of the optical storage system, and C DN (X net ) The total consumption of resources for the operation of the power grid,the Lagrangian multiplier corresponding to the kth iterative process after the equivalent conversion of the power grid operation control model is adopted, ρ is a punishment coefficient, T is an optimization time period number, T is an optimization operation control total time period number, and>the method comprises the steps that the method is an auxiliary variable corresponding to a kth iterative process after the power grid operation control model is equivalently converted, and the I is a two-norm operator; x is X m Controlling a model control variable X for the operation of the optical storage system m ＝[X m (1),...,X m (T)]，X m (t)＝[P m (t),Q m (t)]，P m (t),Q m (t) the intended active power and reactive compensation power respectively transmitted by the optical storage system m to the auxiliary service in the t period,/>Harvesting of the mth optical storage system involved in the grid auxiliary service,/->The Lagrangian multiplier corresponding to the kth iterative process after the equivalent transformation of the optical storage system control model,the auxiliary variable corresponding to the kth iteration process after the equivalent transformation of the optical storage system operation control model is adopted; z is Z k Is an auxiliary variable +.> and />The unified set X is the control variable X of the operation control model of the optical storage system m And grid optimization control model control variable X net Lambda of (x) k As auxiliary variable Z k Lagrangian multipliers corresponding to the kth iterative updating process;
the step S3 comprises the following steps:
s31, setting maximum iteration times and convergence accuracy, and setting upper and lower limits of unit consumption items between the optical storage system and the power gridInitializing a unit compensation item of a power grid to a light storage system to be 0, initializing iteration number k to be 0 and initializing independent variablesInitializing auxiliary variable +.>Initializing the augmented lagrangian multiplier +.>And penalty coefficient ρ 0 Wherein T e [1,2, ], t.]M is M, M is a set formed by all the optical storage systems;
s32, for the main body of the power grid, receiving the active power expected to be distributed to auxiliary services of the power grid from each optical storage systemAnd reactive power->According to the power grid side operation control model, the Lagrangian optimization objective function and the operation constraint are amplified, the distributed optimization model is solved, and the active power +_ expected to be introduced on auxiliary service by the power grid is obtained>And reactive power->
S33, for each optical storage system, receiving the expected active power of the optical storage system from the power gridAnd reactive powerAccording to the operational control model of the optical storage system, the Lagrangian optimization objective function and operational constraint are enhanced, the distributed optimization model is solved, and the output quantity of the optical storage system m responding to the auxiliary service of the power grid is obtained>And reactive compensation quantity->
S34, updating active power reference values of main bodies of all optical storage system power stations in response to auxiliary services of active power distribution networkAnd reactive power reference value->Auxiliary variable->
S35, updating Lagrangian multiplierPenalty coefficient ρ k+1 Update iteration number k=k+1:
wherein ,for self-disability, add->Is the mutual residual error;
s36, calculating the total power of the optical storage system participating in auxiliary serviceCalculating the optical storage system unit compensation term>
Wherein alpha is an attenuation coefficient;
s37, judging whether iteration termination conditions are met according to the mutual residual errors and the self-residual errors of the variables, if yes, ending, otherwise, returning to the step S32.
2. The method according to claim 1, characterized in that the objective function of the grid-side operation control model is in particular as follows:
wherein ,CDN C, running total consumption resources for the power grid loss Consuming resources for network damages of the power grid, C bat Invoking consumed resources of the optical storage system on auxiliary service for the power grid, C pen P is the voltage out-of-limit cost of the power grid node loss (t) is the total loss power of the power grid in the period of t, c t The consumption term is t time period unit, deltat is unit time length, c bat (t) is an optical storage systemThe unit consumption term in the t time period is unified, and omega is the distribution proportionality coefficient of the unit consumption term of the optical storage system on the active and reactive power;respectively crossing upper limit parameters and lower limit parameters of voltage of all voltage nodes of the power grid in a t time period; lambda (lambda) pen And the grid cost coefficient is obtained after the voltage is out of limit.
3. The method according to claim 1, characterized in that the operational constraints of the grid-side operational control model are in particular as follows:
P i min ≤P i (t)≤P i max
wherein ,respectively crossing upper limit parameters and lower limit parameters of voltage of all voltage nodes of the power grid in a t time period, wherein i is the number of the nodes of the power grid, omega is a set formed by the numbers of all the nodes of the power grid, and U is a set of the numbers of the nodes of the power grid max ,U min Respectively the maximum value and the minimum value of the node voltage, U i (t) is the voltage of node i in time period t, P i (t),Q i (t) active power and reactive power limits of the grid node i in the t period, respectively,/->Minimum active power and maximum active power of node i, respectively, +.>Minimum reactive power and maximum reactive power of node i, P j ,Q j Active and reactive power, P, flowing respectively from node j to the node below ij ,Q ij Active power and reactive power flowing to a node j of the power grid node i respectively; r is (r) ij ,x ij Resistance and reactance between node i and node j, respectively, +.>Active and reactive power of the load of node j, respectively,/->Distributed photovoltaic output of node j, < >>The active power and the reactive power of the optical storage system which are respectively called by the power grid to the node j are I as an absolute value operator.
4. The method of claim 1, wherein the objective function of the optical storage system operation control model is specified as follows:
wherein ,cc Resource coefficients are consumed for the unit electric quantity of the optical storage system; Δt is the time interval, || is the absolute value operator.
5. The method of claim 1, wherein the operational constraints of the optical storage system operational control model are specified as follows:
wherein ,reactive compensation power minimum and maximum values for the mth optical storage system in response to the auxiliary service in the t period,/for the mth optical storage system>Respectively mth optical storage systemThe discharge power and the charge power of the medium energy storage in the t time period,respectively, the maximum discharge power and the maximum charge power allowed by energy storage in the mth optical storage system, < +.>For the charge state of energy stored in the mth optical storage system in the t time period, E bat,m Is the maximum capacity of energy storage in the mth optical storage system, delta t is the time interval, eta c,m ,η d,m Respectively the charging and discharging efficiency of the energy storage in the mth optical storage system,/for>Maximum and minimum constraints of the state of charge of the stored energy in the mth optical storage system, respectively,/->The initial charge state and the final charge state of the energy storage in the operation control in the mth optical storage system are respectively.
6. An operation control system for a light storage system participating in a power grid voltage regulation auxiliary service, which is characterized by comprising: a processor and a memory;
the memory is used for storing computer execution instructions;
the processor for executing the computer-executable instructions such that the method of any one of claims 1 to 5 is performed.
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