CN117439109A - Water-fire storage combined frequency modulation method and device - Google Patents
Water-fire storage combined frequency modulation method and device Download PDFInfo
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Abstract
The invention relates to a water-fire storage joint frequency modulation method and a device. The method comprises the following steps: constructing a water-fire storage joint frequency modulation model; constructing a frequency modulation precision target function and a frequency modulation speed target function; acquiring a frequency modulation capacity allocation scheme meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set; respectively obtaining a solution with highest frequency modulation precision and highest frequency modulation speed as a first initial solution and a second initial solution, and iteratively obtaining a local optimal Pareto solution set by using a greedy algorithm and respectively taking optimal frequency modulation precision objective function and optimal frequency modulation speed objective function as optimization targets; calculating the crowding degree of each solution, taking the lowest crowding degree as a third initial solution, and iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target to obtain a plurality of non-dominant solutions; calculating and obtaining the non-dominant solution with the biggest HV index in all the non-dominant solutions as an optimal solution; and (3) performing frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of the optimal solution.
Description
Technical Field
The invention relates to the technical field of frequency modulation, in particular to a water-fire storage joint frequency modulation method and device.
Background
The renewable energy source grid-connected proportion is increased, and challenges are brought to the frequency stability of the power grid. In order to cope with the uncertainty of frequency fluctuation, an energy storage system is added in the traditional thermal power frequency modulation and hydroelectric frequency modulation to assist in frequency modulation, so that the thermal power frequency modulation and hydroelectric frequency modulation become hot spots. When the power grid load changes greatly, the traditional thermal power plant cannot respond quickly, and the energy storage equipment has the advantages of quick response, short response time and high adjustment precision, and the combined water and fire storage frequency modulation system can better cope with frequency modulation requirements and keep the power grid frequency stable.
The existing water and fire energy storage frequency modulation technology is concentrated on controlling the speed regulator of a thermal power unit, the speed regulator of a water pump and water turbine and the like to regulate the capacity of the water and fire machine set to participate in frequency modulation, or adopts algorithms such as particle swarm algorithm and the like to distribute the output of each frequency modulation source aiming at frequency mutation caused by load cut-in and cut-out.
The water and fire storage data is relatively stable, and when real-time scheduling in the day is performed, the change of the power demand needs to be responded quickly. However, the response speed of the existing water-fire storage frequency modulation technology is relatively slow, and transient load changes cannot be rapidly dealt with; for example, when the particle swarm algorithm is used for solving complex problems, the problems of insufficient optimization precision, low convergence speed and the like exist.
In summary, the existing water-fire frequency modulation method cannot allocate the frequency modulation power of each frequency modulation source in real time, has long frequency modulation response time, cannot fully utilize the frequency modulation capability of each frequency modulation source, and has poor frequency modulation precision.
Disclosure of Invention
Therefore, the invention aims to solve the technical problems of long frequency modulation response time and poor frequency modulation precision in the prior art.
In order to solve the technical problems, the invention provides a water-fire storage joint frequency modulation method, which comprises the following steps:
presetting a water and fire storage system frequency modulation parameter, constructing a water and fire storage combined frequency modulation model, and collecting water and fire unit operation data and power grid state data;
constructing a frequency modulation precision target function and a frequency modulation speed target function;
acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set;
obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions;
obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set;
based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set;
calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
and performing frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
In one embodiment of the present invention, the presetting of the frequency modulation parameters of the water and fire storage system, and constructing the water and fire storage joint frequency modulation model, include:
the water and fire storage system frequency modulation parameters comprise upper frequency modulation output limit and lower frequency modulation output limit of each frequency modulation source in the water and fire storage system, output time period, average frequency modulation error, average frequency modulation speed, upper energy storage SOC limit and lower energy storage SOC limit, energy storage charging efficiency and discharging efficiency;
the water and fire storage joint frequency modulation model comprises:
the unit output constraint is expressed as:wherein P is i Representing the FM output, P, of an i-th type of FM source i Representing the lower limit of the FM output of the i-th type of FM source, P i Representing the upper limit of the frequency modulation output of the i-th frequency modulation source; i is { T, H, EES }, T represents a thermal power unit frequency modulation source, H represents a hydroelectric power unit frequency modulation source, and EES represents an energy storage system frequency modulation source;
energy storage SOC constraints, expressed as:s (t) represents the SOC value of the energy storage system at the end of the t output period, and delta S (t) represents the variation of the SOC value of the energy storage system in the t output period; η (eta) c And eta d Respectively representing the charging efficiency and the discharging efficiency of the energy storage system, P c And P d Respectively representing the charging power and the discharging power of the energy storage system, delta t represents the frequency modulation time step length, E rate Representing the rated power of the energy storage system; s is S max And S is equal to min Respectively representing an upper energy storage SOC limit and a lower energy storage SOC limit;
respectively representing the voltage phase angles h of a node l and a node j in the water-fire storage joint frequency modulation model lj,max Representing the power limit, θ, of node l and node j j.max Representing phase angle limit, x lj Representing the reactance of node l and node j, θ ref,t Representing a balanced node phase angle; g represents a set of units connected with the node j, F represents a line set taking the node j as a starting point, and E represents a line set taking the node j as an ending point; f (f) lj,t Representing the power flow of the line (l, j) from node l to node j, positive and negative representing the direction of the power flow; d (D) j,t Representing the electrical load demand of node j.
In one embodiment of the invention, the water-fire unit operation data comprises output voltage, output current, output power, steam turbine rotation speed and water turbine rotation speed of the thermal power unit and the hydroelectric power unit; the power grid state data comprise frequency modulation precision instructions and frequency modulation speed instructions in each frequency modulation source frequency modulation capacity allocation scheme in the water storage system, power grid frequency deviation and historical region control errors.
In one embodiment of the present invention, the constructing the tuning accuracy objective function and the tuning speed objective function includes:
frequency modulation speed objective function J 1 Expressed as:
frequency modulation precision objective function J 2 Expressed as:
wherein M is the total number of frequency modulation sources in the water and fire storage system, and P m The frequency modulation output of the mth frequency modulation source, v m Frequency modulation speed of mth frequency modulation source, q m For the tuning accuracy of the mth tuning source, m=1, 2.
In one embodiment of the present invention, the obtaining, by using an equalization heuristic algorithm, a frequency modulation capacity allocation scheme of each frequency modulation source in a water and fire storage system that meets a preset equalization constraint, to form an initial Pareto solution set includes:
the preset equilibrium constraint is:beta represents an equalization coefficient, C m Represents the frequency modulation capacity, P, of the mth frequency modulation source m Representing the frequency modulation output of the mth frequency modulation source;
randomly distributing the frequency modulation capacity to each frequency modulation source, and judging whether the distribution scheme meets the equilibrium constraint:
if the equilibrium constraint is met, ending the distribution, and obtaining the distribution scheme as an initial Pareto solution;
if the balance constraint is not met, adjusting the frequency modulation power distributed by the high frequency modulation load rate unit to the low frequency modulation load rate unit until a frequency modulation capacity distribution scheme meeting the balance constraint is output, and acquiring the distribution scheme as an initial Pareto solution;
and (3) combining all frequency modulation capacity allocation schemes with the output meeting the balance constraint into an initial Pareto solution set.
In one embodiment of the present invention, the calculating the congestion degree of each solution based on the locally optimal Pareto solution set, taking the solution with the lowest congestion degree as the third initial solution, iterating with the greedy algorithm and taking the lowest congestion degree as the optimization target, obtaining the non-dominant solution, and generating the updated Pareto solution set includes:
initializing congestion degree parameter m d ＝0，m＝1,2,3，…，M；
Respectively according to the frequency modulation precision objective function J 2 With the frequency modulation speed objective function J 1 Sorting the solutions in the locally optimal Pareto solution set;
setting the congestion degree 1 of the minimum boundary value after sequencing d Congestion degree M with maximum boundary value d Are all ≡infinity;
calculating the congestion degree value of each solution after sequencing, which is expressed as m d ：
Wherein n=2; when n=1, the number of the n-type switches,indicating the frequency modulation speed J 1 Maximum value of>Represents J 1 Is the minimum of (2); when n=2, _a->Representing the frequency modulation accuracy J 2 Maximum value of>Represents J 2 Is the minimum of (2);
and (3) taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining a non-dominant solution, and generating an updated Pareto solution set.
In one embodiment of the invention, the HV indicator is expressed as:
where δ represents the Lebesgue measure, |s| represents the number of non-dominant solutions, v i Representing the supersvolume formed by the reference point of the preset frequency modulation capacity allocation scheme and the ith non-dominant solution.
In one embodiment of the invention, the water and fire storage system comprises a thermal power unit frequency control system, a hydroelectric power unit frequency control system and an energy storage battery energy management system which are respectively used for controlling the thermal power unit, the hydroelectric power unit and the energy storage system.
In one embodiment of the present invention, the frequency modulation method for the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution includes: and controlling the thermal power generating unit frequency control system, the hydroelectric generating unit frequency control system and the energy storage battery energy management system to execute the optimal frequency modulation instruction.
The embodiment of the invention also provides a water-fire storage joint frequency modulation device, which comprises:
the model construction and data acquisition module is used for presetting water and fire storage system frequency modulation parameters, constructing a water and fire storage combined frequency modulation model and acquiring water and fire unit operation data and power grid state data;
the greedy decision module is used for constructing a frequency modulation precision objective function and a frequency modulation speed objective function; acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set; obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions; obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set; based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set; calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
and the execution module is used for carrying out frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
Compared with the prior art, the technical scheme of the invention has the following advantages:
according to the water-fire storage combined frequency modulation method, the frequency modulation characteristics of the water-fire storage frequency modulation system are considered, and the distribution scheme of the frequency modulation capacity is gradually optimized by adopting a balanced heuristic algorithm and a greedy algorithm so as to meet balanced constraint conditions, so that the load rate distribution of a frequency modulation source in the final distribution scheme is more balanced, and the frequency modulation stability and performance are improved; on the premise of meeting multi-objective optimization, the greedy algorithm rapidly acquires the optimal solution, and improves the decision efficiency and practicality. According to the invention, the congestion degree sequencing and the HV index are used for comprehensively considering the frequency modulation precision and the frequency modulation speed, so that balance is achieved among different objective functions, and an optimal solution considering the frequency modulation precision and the frequency modulation speed is obtained; and the water and fire storage system is subjected to frequency modulation according to the optimal solution, so that the frequency modulation power among all frequency modulation sources is optimally distributed, the frequency modulation precision and the frequency modulation speed of the water and fire storage system are improved, and more reliable support is provided for the stable operation of the power system.
Drawings
In order that the invention may be more readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof that are illustrated in the appended drawings, in which
FIG. 1 is a flow chart of the steps of the water-fire storage joint frequency modulation method of the invention;
FIG. 2 is a diagram showing the implementation steps of the water-fire storage joint frequency modulation method of the invention;
FIG. 3 is a diagram of an EEE39 model wiring diagram provided by the present invention;
FIG. 4 is a graph of thermal power plant output of the present invention;
FIG. 5 is a graph of historical area control error for the present invention;
FIG. 6 is a flow chart of the equalization heuristic of the present invention;
FIG. 7 is a flow chart of the greedy algorithm of the present invention;
FIG. 8 is a schematic diagram showing steps for calculating the congestion level according to the present invention;
FIG. 9 is a schematic diagram of a thermal power generating unit frequency control system of the present invention;
FIG. 10 is a schematic diagram of a hydroelectric generating set frequency control system of the present invention;
FIG. 11 is a schematic diagram of the water-fire storage joint frequency modulation device of the invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples, which are not intended to be limiting, so that those skilled in the art will better understand the invention and practice it.
Referring to fig. 1, the step flow chart of the water-fire storage combined frequency modulation method of the invention specifically comprises the following steps:
s101: presetting a water and fire storage system frequency modulation parameter, constructing a water and fire storage combined frequency modulation model, and collecting water and fire unit operation data and power grid state data;
the water-fire unit operation data comprise output voltage, output current, output power, steam turbine rotating speed and water turbine rotating speed of the thermal power unit and the hydroelectric power unit;
the power grid state data comprise frequency modulation precision instructions and frequency modulation speed instructions in each frequency modulation source frequency modulation capacity allocation scheme in the water storage system, power grid frequency deviation and historical region control errors;
s102: constructing a frequency modulation precision target function and a frequency modulation speed target function;
s103: acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set;
s104: obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions;
s105: obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set;
s106: based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set;
s107: calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
s108: and performing frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
Specifically, in step S101, the frequency modulation parameters of the water and fire storage system include an upper frequency modulation output limit and a lower frequency modulation output limit of each frequency modulation source in the water and fire storage system, an output period, an average frequency modulation error, an average frequency modulation speed, an upper energy storage SOC limit and a lower energy storage SOC limit, and an energy storage charging efficiency and a discharging efficiency;
the water and fire storage joint frequency modulation model comprises:
the unit output constraint is expressed as:wherein P is i Representing the fm output of the class i fm source,P i lower limit of FM output representing class i FM source, < ->Representing the upper limit of the frequency modulation output of the i-th frequency modulation source; i is { T, H, EES }, T represents a thermal power unit frequency modulation source, H represents a hydroelectric power unit frequency modulation source, and EES represents an energy storage system frequency modulation source;
energy storage SOC constraints, expressed as:s (t) represents the SOC value of the energy storage system at the end of the t output period, and delta S (t) represents the variation of the SOC value of the energy storage system in the t output period; η (eta) c And eta d Respectively representing the charging efficiency and the discharging efficiency of the energy storage system, P c And P d Respectively representing the charging power and the discharging power of the energy storage system, delta t represents the frequency modulation time step length, E rate Representing the rated power of the energy storage system; s is S max And S is equal to min Respectively representing an upper energy storage SOC limit and a lower energy storage SOC limit;
the power flow constraint and the node voltage constraint are expressed as:-θ j.max ≤θ j,t ≤θ j.max ，θ ref,t ＝0，/>wherein θ l,t And theta j,t Respectively representing the voltage phase angles h of a node l and a node j in the water-fire storage joint frequency modulation model lj,max Representing the power limit, θ, of node l and node j j.max Representing phase angle limit, x lj Representing the reactance of node l and node j, θ ref,t Representing a balanced node phase angle; g represents a set of units connected with the node j, F represents a line set taking the node j as a starting point, and E represents a line set taking the node j as an ending point; f (f) lj,t Representing the power flow of the line (l, j) from node l to node j, positive and negative representing the direction of the power flow; d (D) j,t Representing the electrical load demand of node j.
Specifically, in step S102, a frequency modulation speed objective function and a frequency modulation precision objective function are constructed, which specifically includes:
frequency modulation speed objective function J 1 Expressed as:
frequency modulation precision objective function J 2 Expressed as:
wherein M is the total number of frequency modulation sources in the water and fire storage system, and P m The frequency modulation output of the mth frequency modulation source, v m Frequency modulation speed of mth frequency modulation source, q m For the tuning accuracy of the mth tuning source, m=1, 2.
Specifically, in step S103, the acquisition of the initial Pareto solution set includes:
s103-1: the preset equilibrium constraint is:beta represents an equalization coefficient, C m Represents the frequency modulation capacity, P, of the mth frequency modulation source m Representing the frequency modulation output of the mth frequency modulation source;
s103-2: randomly distributing the frequency modulation capacity to each frequency modulation source, and judging whether the distribution scheme meets the equilibrium constraint:
if the equilibrium constraint is met, ending the distribution, and obtaining the distribution scheme as an initial Pareto solution;
if the balance constraint is not met, adjusting the frequency modulation power distributed by the high frequency modulation load rate unit to the low frequency modulation load rate unit until a frequency modulation capacity distribution scheme meeting the balance constraint is output, and acquiring the distribution scheme as an initial Pareto solution;
s103-3: and (3) combining all frequency modulation capacity allocation schemes with the output meeting the balance constraint into an initial Pareto solution set.
Specifically, in step S106, the updating of the acquisition of the Pareto solution set includes:
s106-1: initializing congestion degree parameter m d ＝0，m＝1,2,3，…，M；
S106-2: respectively according to the frequency modulation precision objective function J 2 With the frequency modulation speed objective function J 1 Sorting the solutions in the locally optimal Pareto solution set;
s106-3: setting the congestion degree 1 of the minimum boundary value after sequencing d Congestion degree M with maximum boundary value d Are all ≡infinity;
s106-4: calculating the congestion degree value of each solution after sequencing, which is expressed as m d ：
Wherein n=2; when n=1, the number of the n-type switches,indicating the frequency modulation speed J 1 Maximum value of>Indicating the frequency modulation speed J 1 Is the minimum of (2); when n=2, _a->Representing the frequency modulation accuracy J 2 Maximum value of>Representing the frequency modulation accuracy J 2 Is the minimum of (2);
s106-5: and (3) taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining a non-dominant solution, and generating an updated Pareto solution set.
Specifically, in step S107, the HV indicator is expressed asWhere δ represents the Lebesgue measure, |s| represents the number of non-dominant solutions, v i Representing the supersvolume formed by the reference point of the preset frequency modulation capacity allocation scheme and the ith non-dominant solution.
According to the water-fire storage combined frequency modulation method, the frequency modulation characteristics of the water-fire storage frequency modulation system are considered, and the distribution scheme of the frequency modulation capacity is gradually optimized by adopting a balanced heuristic algorithm and a greedy algorithm so as to meet balanced constraint conditions, so that the load rate distribution of a frequency modulation source in the final distribution scheme is more balanced, and the frequency modulation stability and performance are improved; on the premise of meeting multi-objective optimization, the greedy algorithm rapidly acquires the optimal solution, and improves the decision efficiency and practicality. According to the invention, the congestion degree sequencing and the HV index are used for comprehensively considering the frequency modulation precision and the frequency modulation speed, so that balance is achieved between different objective functions, an optimal solution considering the frequency modulation precision and the frequency modulation speed is obtained, and the frequency modulation precision and the frequency modulation speed of the water and fire storage system are improved.
Referring to fig. 2, based on the above embodiment, in this embodiment, a water-fire storage joint frequency modulation model is constructed based on the IEEE39 model shown in fig. 3, and the water-fire storage joint frequency modulation is performed, which specifically includes:
s201: setting frequency modulation parameters of a water and fire storage system, and constructing a water and fire storage combined frequency modulation model;
in this embodiment, the frequency modulation parameters of the water and fire frequency modulation sources include upper and lower limits of the frequency modulation output, average frequency modulation error and average frequency modulation speed of each frequency modulation source, and the parameters are shown in table 1:
table 1 Water and fire frequency modulation Source parameter settings
In the embodiment, the upper limit of the frequency modulation output of the two energy storage systems is 12MW, the lower limit of the frequency modulation output is-12 MW, and the charge and discharge efficiency eta c 、η d 0.94 and a capacity of 14 MW.h.
In this embodiment, the multisource frequency modulation model includes a unit output constraint, an output period constraint and an energy storage SOC constraint:
wherein P is T 、P H 、P ESS The output of the fire water storage frequency modulation module is respectively,P T 、P H 、P ESS respectively the lower output limit of the corresponding module,the upper limits of the output force of the corresponding modules are respectively set; t represents the output time period, and Δt is the frequency modulation time step; s and delta S respectively represent the SOC value and the variation of the energy storage unit; p (P) c 、P d Respectively representing the charging power and the discharging power of the energy storage unit; e (E) rate Representing the rated power of the energy storage unit; s is S min 、S max Representing a lower and upper SOC limit, respectively.
In the multi-source frequency modulation system, the power flow constraint and the node voltage constraint of the power grid system are also considered:
wherein θ l,t And theta j,t Respectively representing the voltage phase angles h of a node l and a node j in the water-fire storage joint frequency modulation model lj,max Representing the power limit, θ, of node l and node j j.max Representing phase angle limit, x lj Representing the reactance of node l and node j, θ ref,t Representing a balanced node phase angle; g represents a set of units connected with the node j, F represents a line set taking the node j as a starting point, and E represents a line set taking the node j as an ending point; f (f) lj,t Representing the power flow of the line (l, j) from node l to node j, positive and negative representing the direction of the power flow; d (D) j,t Representing the power load demand of node j;
s202, collecting data of a power supply side and a power grid side;
in the embodiment, the power supply side and power grid side data comprise data such as an automatic power generation system frequency modulation instruction, a historical region control error and a frequency deviation, the power supply side thermal power unit output and the like, and the time resolution of the data is 5min; referring to FIG. 4, a graph of thermal power unit output is shown; referring to fig. 5, a history zone control error graph is shown.
S203, determining a frequency modulation precision target function and a frequency modulation speed target function;
in this embodiment, the frequency modulation objective function is:
wherein v is T 、v H 、v ESS Average frequency modulation speed, q of thermal power generating unit, hydroelectric generating unit and energy storage system respectively T 、q H 、q ESS The average frequency modulation precision of the thermal power generating unit, the hydroelectric generating unit and the energy storage system is respectively obtained.
S204: distributing the output of each frequency modulation source by using an equalization heuristic algorithm to construct an initial Pareto solution set; referring to fig. 6, a flowchart of an equalization heuristic algorithm is shown, which specifically includes:
s204-1: setting equalization constraint:
wherein beta is an equilibrium coefficient, C m Is the frequency modulation capacity of the mth frequency modulation source.
S204-2: randomly distributing the frequency modulation capacity to each frequency modulation source;
s204-3: if the allocation scheme meets the balance constraint, ending the algorithm, otherwise, adjusting the allocated frequency modulation power of the high frequency modulation load rate unit to the low frequency modulation load rate unit;
s204-4: all frequency modulation capacity allocation schemes meeting the equilibrium constraint are set as an initial Pareto solution set.
S205: a greedy algorithm is applied to solve and store non-dominant solutions, and a local optimal Pareto solution set is stored; referring to fig. 7, a flow chart of a greedy algorithm is shown, and specific steps include:
s205-1: ordering all frequency modulation sources according to frequency modulation precision from high to low to generate an initial solution x 1 ；
S205-2: ordering all frequency modulation sources from low to high according to response time to generate initial solution x 2 ；
S205-3: from x respectively 1 、x 2 Starting, a greedy algorithm is applied to solve and retain non-dominant solutions to a locally optimal Pareto solution set.
Non-dominant solution means that in a multi-objective optimization problem, one solution is not inferior to another solution on all objectives and is superior to another solution on at least one objective, with the non-dominant solution constituting a set of alternative solutions.
S206: updating the local optimal Pareto solution set according to the congestion degree sequence, and acquiring an updated Pareto solution set;
in the present embodiment, in order to make the obtained solution more uniform in the target space, the congestion degree m is introduced d As shown in fig. 8, the congestion degree calculation step is:
s206-1, initializing parameter m d ＝0，m＝1,2,3，...，M；
S206-2 according to the objective function J 1 、J 2 The solutions are ordered in a sequence that is,respectively two objective function values J 1 、J 2 Maximum value of>Respectively two objective function values J 1 、J 2 Is the minimum of (2);
s206-3, the congestion degree of the two boundaries after sequencing is 1 d 、M d Respectively setting the two values as ++;
s206-4, calculating the sorted congestion degree value:
wherein J is 1 (i-1)、J 1 (i+1) is the first objective function value of the previous bit and the next bit after the solution is ordered, namely the frequency modulation speed value; j (J) 2 (i-1)、J 2 (i+1) is the second objective function value of the previous bit and the next bit after the ordering of the solution, i.e. the frequency modulation precision value.
And selecting the solution with the lowest crowding degree from the locally optimal Pareto solution set as the current solution, applying an iterative greedy algorithm, searching by taking the lowest crowding degree as an optimization target, and acquiring an updated Pareto solution set.
S207: selecting an optimal solution by using the HV evaluation index;
in this embodiment, the HV evaluation index represents the volume of a hypercube surrounded by the Pareto solution and the reference point in the target space, and the larger the hypercube, the better the convergence and diversity of the solution set. The HV evaluation index calculation method comprises the following steps:
wherein δ is the Lebesgue measure for measuring volume; |s| represents the number of non-dominant solutions; v i Representing the supersvolume formed by the reference point of the preset frequency modulation capacity allocation scheme and the ith non-dominant solution.
The reference point is a self-set solution for evaluating the improvement degree of each non-dominant solution to the reference point solution after the solution by the multi-objective greedy algorithm. The larger the supersvolume means that the non-dominant solution improves in tuning accuracy and tuning speed compared to the reference point solution. In this embodiment, the preset reference point of the fm capacity allocation scheme is set as an allocation scheme for performing fm output allocation by using the installed capacity ratio.
S208: and the execution module controls the water and fire storage system to execute the frequency modulation instruction of the optimal solution.
The water and fire storage system comprises a thermal power unit frequency control system, a hydroelectric power unit frequency control system and an energy storage battery energy management system, and the water and fire storage system is respectively used for controlling a speed regulating mechanism of the thermal power unit, a unit controller of the hydroelectric power unit and the energy storage system to execute optimal frequency modulation instructions.
Referring to fig. 9, a schematic diagram of a thermal power generating unit frequency control system is shown; the dispatching center control system controls the unit coordination control system to call the thermal power unit to execute corresponding frequency modulation instructions through the data of the power grid side, and controls the output of the thermal power unit through controlling the working frequency of the thermal power unit.
Referring to fig. 10, a schematic diagram of a hydroelectric generating set frequency control system is shown; the automatic power generation control system of the hydroelectric generating set and the automatic power generation control system of the thermal power generating set have great differences in many aspects, and because of the difference of power generation modes, the composition and regulation modes of the generating sets are different, for example, the water turbine can be influenced by the water hammer effect, and the thermal power is not. The water turbine converts potential energy of water into mechanical energy, and then drives the generator to generate electricity. The speed regulator achieves the purpose of controlling the power generation frequency by controlling the rotating speed of the water turbine, and further participates in the frequency modulation of the power grid.
In the energy storage system, the energy storage of the lithium battery is monitored in real time, fault diagnosis and charge and discharge control are carried out through the energy storage battery energy management system.
According to the water and fire frequency modulation method, the frequency modulation characteristics of the water and fire frequency modulation system are considered, the energy storage system is designed to assist the water and fire frequency modulation system in secondary frequency modulation, the frequency modulation power of each frequency modulation source is distributed by adopting a balanced heuristic algorithm and an iterative greedy algorithm, the frequency modulation precision and the frequency modulation speed of the system are comprehensively considered by using crowdedness sequencing and HV evaluation indexes, the frequency modulation power among the frequency modulation sources is optimally distributed, and the frequency modulation precision and the frequency modulation speed of the multi-source frequency modulation system are improved.
Based on the above embodiment, in this embodiment, the present invention further provides a water-fire storage joint frequency modulation device, including:
the model construction and data acquisition module comprises a thermal power unit operation data acquisition device, a hydroelectric power unit operation data acquisition device and a power grid state data acquisition device; the thermal power unit operation data acquisition device acquires data such as output voltage, output current, output power, steam turbine rotating speed, water turbine rotating speed and the like of the thermal power unit and the hydroelectric power unit in real time; the power grid state data acquisition device acquires and calculates data such as power grid frequency deviation, regional control error and the like in real time;
setting a frequency modulation objective function in the greedy decision module, solving and storing non-dominant solutions of the output force of each frequency modulation source by applying a balanced heuristic algorithm module and an iterative greedy algorithm module, storing the non-dominant solutions in a Pareto solution set, and updating the Pareto solution set according to a crowdedness ordering module; finally, selecting an optimal solution by applying the HV evaluation module, and inputting the optimal solution into the execution module;
the execution module comprises a thermal power unit frequency control system, a hydroelectric unit frequency control system and an energy storage battery energy management system; the execution module controls the frequency modulation output of the thermal power generating unit, the hydroelectric system and the energy storage system according to the optimal solution input by the greedy decision module, completes the secondary frequency modulation optimal control, balances the frequency modulation output of each unit and improves the frequency modulation precision and the frequency modulation speed of the secondary frequency modulation.
Specifically, referring to fig. 11, the water-fire storage joint frequency modulation device includes:
the model construction and data acquisition module 100 is used for presetting water and fire storage system frequency modulation parameters, constructing a water and fire storage combined frequency modulation model and acquiring water and fire unit operation data and power grid state data;
the greedy decision module 200 is used for constructing a frequency modulation precision objective function and a frequency modulation speed objective function; acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set; obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions; obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set; based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set; calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
and the execution module 300 is used for performing frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
The water-fire storage joint frequency modulation device of the present embodiment is used for implementing the foregoing water-fire storage joint frequency modulation method, so that the specific implementation in the water-fire storage joint frequency modulation device can be seen as the example part of the water-fire storage joint frequency modulation method in the foregoing, for example, the model building and data acquisition module 100 is used for implementing step S101 in the foregoing water-fire storage joint frequency modulation method; the greedy decision module 200 is configured to implement steps S101, S102, S103, S104, S105, S106 and S107 in the above-mentioned water-fire storage joint frequency modulation method; the execution module 300 is configured to implement step S108 in the water-fire storage joint frequency modulation method; therefore, the specific embodiments thereof may refer to the descriptions of the corresponding examples of the respective parts, and will not be repeated herein.
According to the water-fire storage combined frequency modulation method, the frequency modulation characteristics of the water-fire storage frequency modulation system are considered, and the distribution scheme of the frequency modulation capacity is gradually optimized by adopting a balanced heuristic algorithm and a greedy algorithm so as to meet balanced constraint conditions, so that the load rate distribution of a frequency modulation source in the final distribution scheme is more balanced, and the frequency modulation stability and performance are improved; on the premise of meeting multi-objective optimization, the greedy algorithm rapidly acquires an optimal solution, distributes water and fire storage frequency modulation power in real time, reduces frequency modulation time while increasing control precision, fully utilizes the frequency modulation capability of each frequency modulation source, and improves decision efficiency and practicality. According to the invention, the congestion degree sequencing and the HV index are used for comprehensively considering the frequency modulation precision and the frequency modulation speed, so that balance is achieved among different objective functions, and an optimal solution considering the frequency modulation precision and the frequency modulation speed is obtained; and the water and fire storage system is subjected to frequency modulation according to the optimal solution, frequency modulation power among all frequency modulation sources is optimally distributed, response time and frequency deviation of the frequency modulation system are reduced while the output balance of the frequency modulation unit is maintained, frequency modulation precision and frequency modulation speed of the water and fire storage system are improved, and more reliable support is provided for stable operation of the power system.
It will be appreciated by those skilled in the art that 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations and modifications of the present invention will be apparent to those of ordinary skill in the art in light of the foregoing description. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (10)
1. The water and fire storage joint frequency modulation method is characterized by comprising the following steps of:
presetting a water and fire storage system frequency modulation parameter, constructing a water and fire storage combined frequency modulation model, and collecting water and fire unit operation data and power grid state data;
constructing a frequency modulation precision target function and a frequency modulation speed target function;
acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set;
obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions;
obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set;
based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set;
calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
and performing frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
2. The water-fire storage joint frequency modulation method according to claim 1, wherein the preset water-fire storage system frequency modulation parameters construct a water-fire storage joint frequency modulation model, and the method comprises the following steps:
the water and fire storage system frequency modulation parameters comprise upper frequency modulation output limit and lower frequency modulation output limit of each frequency modulation source in the water and fire storage system, output time period, average frequency modulation error, average frequency modulation speed, upper energy storage SOC limit and lower energy storage SOC limit, energy storage charging efficiency and discharging efficiency;
the water and fire storage joint frequency modulation model comprises:
the unit output constraint is expressed as:wherein P is i Representing the fm output of the class i fm source,P i lower limit of FM output representing class i FM source, < ->Representing the upper limit of the frequency modulation output of the i-th frequency modulation source; i is { T, H, EES }, T represents a thermal power unit frequency modulation source, H represents a hydroelectric power unit frequency modulation source, and EES represents an energy storage system frequency modulation source;
energy storage SOC constraints, expressed as:s (t) represents the SOC value of the energy storage system at the end of the t output period, and delta S (t) represents the variation of the SOC value of the energy storage system in the t output period; η (eta) c And eta d Respectively representing the charging efficiency and the discharging efficiency of the energy storage system, P c And P d Respectively representing the charging power and the discharging power of the energy storage system, delta t represents the frequency modulation time step length, E rate Representing the rated power of the energy storage system; s is S max And S is equal to min Respectively representing an upper energy storage SOC limit and a lower energy storage SOC limit;
the power flow constraint and the node voltage constraint are expressed as:-θ j.max ≤θ j,t ≤θ j.max ，θ ref,t ＝0，/>wherein θ l,t And theta j,t Respectively representing the voltage phase angles h of a node l and a node j in the water-fire storage joint frequency modulation model lj,max Representing the power limit, θ, of node l and node j j.max Representing phase angle limit, x lj Representing the reactance of node l and node j, θ ref,t Representing a balanced node phase angle; g represents a set of units connected with the node j, F represents a line set taking the node j as a starting point, and E represents a line set taking the node j as an ending point; f (f) lj,t Representing the power flow of the line (l, j) from node l to node j, positive and negative representing the direction of the power flow; d (D) j,t Representing the electrical load demand of node j.
3. The water-fire storage joint frequency modulation method according to claim 1, wherein the water-fire unit operation data comprise output voltage, output current, output power, steam turbine rotation speed and water turbine rotation speed of a thermal power unit and a hydroelectric power unit; the power grid state data comprise frequency modulation precision instructions and frequency modulation speed instructions in each frequency modulation source frequency modulation capacity allocation scheme in the water storage system, power grid frequency deviation and historical region control errors.
4. The water-fire-storage combined frequency modulation method according to claim 1, wherein the constructing the frequency modulation precision objective function and the frequency modulation speed objective function comprises:
frequency modulation speed objective function J 1 Expressed as:
frequency modulation precision objective function J 2 Expressed as:
wherein M is the total number of frequency modulation sources in the water and fire storage system, and P m The frequency modulation output of the mth frequency modulation source, v m Frequency modulation speed of mth frequency modulation source, q m For the tuning accuracy of the mth tuning source, m=1, 2.
5. The method for combined frequency modulation of water and fire storage according to claim 1, wherein the obtaining the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting the preset equilibrium constraint by using the equilibrium heuristic algorithm, to form an initial Pareto solution set, comprises:
the preset equilibrium constraint is:beta represents an equalization coefficient, C m Representing the mth frequency-modulated sourceFrequency modulation capacity, P m Representing the frequency modulation output of the mth frequency modulation source;
randomly distributing the frequency modulation capacity to each frequency modulation source, and judging whether the distribution scheme meets the equilibrium constraint:
if the equilibrium constraint is met, ending the distribution, and obtaining the distribution scheme as an initial Pareto solution;
if the balance constraint is not met, adjusting the frequency modulation power distributed by the high frequency modulation load rate unit to the low frequency modulation load rate unit until a frequency modulation capacity distribution scheme meeting the balance constraint is output, and acquiring the distribution scheme as an initial Pareto solution;
and (3) combining all frequency modulation capacity allocation schemes with the output meeting the balance constraint into an initial Pareto solution set.
6. The water-fire storage joint frequency modulation method according to claim 1, wherein the calculating the congestion degree of each solution based on the locally optimal Pareto solution set, taking the solution with the lowest congestion degree as a third initial solution, iterating with a greedy algorithm with the lowest congestion degree as an optimization target to obtain a non-dominant solution, and generating an updated Pareto solution set includes:
initializing congestion degree parameter m d ＝0，m＝1,2,3，…，M；
Respectively according to the frequency modulation precision objective function J 2 With the frequency modulation speed objective function J 1 Sorting the solutions in the locally optimal Pareto solution set;
setting the congestion degree 1 of the minimum boundary value after sequencing d Congestion degree M with maximum boundary value d Are all ≡infinity;
calculating the congestion degree value of each solution after sequencing, which is expressed as m d ：
Wherein n=2; when n=1, the number of the n-type switches,indicating the frequency modulation speed J 1 Maximum value of>Represents J 1 Is the minimum of (2); when n=2, the number of the n-type groups,representing the frequency modulation accuracy J 2 Maximum value of>Represents J 2 Is the minimum of (2);
and (3) taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining a non-dominant solution, and generating an updated Pareto solution set.
7. The water-fire storage joint frequency modulation method according to claim 1, wherein the HV indicator is expressed as:
where δ represents the Lebesgue measure, |s| represents the number of non-dominant solutions, v i Representing the supersvolume formed by the reference point of the preset frequency modulation capacity allocation scheme and the ith non-dominant solution.
8. The water-fire storage joint frequency modulation method according to claim 1, wherein the water-fire storage system comprises a thermal power unit frequency control system, a hydroelectric power unit frequency control system and an energy storage battery energy management system, and the water-fire storage system is used for controlling the thermal power unit, the hydroelectric power unit and the energy storage system respectively.
9. The method for combined frequency modulation of water and fire storage according to claim 8, wherein the frequency modulation of the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution comprises: and controlling the thermal power generating unit frequency control system, the hydroelectric generating unit frequency control system and the energy storage battery energy management system to execute the optimal frequency modulation instruction.
10. A water and fire storage joint frequency modulation device, comprising:
the model construction and data acquisition module is used for presetting water and fire storage system frequency modulation parameters, constructing a water and fire storage combined frequency modulation model and acquiring water and fire unit operation data and power grid state data;
the greedy decision module is used for constructing a frequency modulation precision objective function and a frequency modulation speed objective function; acquiring a frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system meeting preset equilibrium constraint by using an equilibrium heuristic algorithm to form an initial Pareto solution set; obtaining the solution with the highest frequency modulation precision in the initial Pareto solution set as a first initial solution, and carrying out iteration by using a greedy algorithm and taking the frequency modulation precision objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of precision local optimal solutions; obtaining the solution with the highest frequency modulation speed in the initial Pareto solution set as a second initial solution, and iterating by using a greedy algorithm and taking the frequency modulation speed objective function as an optimization target until the preset iteration times are reached, so as to obtain a plurality of speed local optimal solutions and a plurality of precision local optimal solutions to form a local optimal Pareto solution set; based on the local optimal Pareto solution set, calculating the crowding degree of each solution, taking the solution with the lowest crowding degree as a third initial solution, iterating by using a greedy algorithm and taking the lowest crowding degree as an optimization target, obtaining non-dominant solutions, and generating an updated Pareto solution set; calculating the HV (high voltage) index of each non-dominant solution in the updated Pareto solution set and a preset frequency modulation capacity allocation scheme reference point, and obtaining the non-dominant solution with the largest HV index as an optimal solution;
and the execution module is used for carrying out frequency modulation on the water and fire storage system based on the frequency modulation capacity allocation scheme of each frequency modulation source in the water and fire storage system represented by the optimal solution.
Priority Applications (1)
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