A multi-region decomposition coordination optimization scheduling method, device and storage medium

Abstract

The present invention discloses a multi-region decomposition coordinated optimization scheduling method, device and storage medium. The method comprises: performing augmented Lagrangian relaxation on the coupling relationship between each adjacent sub-region according to the constraint conditions and objective function of each sub-region to obtain the first augmented Lagrangian function of each sub-region; and using the AMMD algorithm to calculate the first tie-line flow of each sub-region according to the first augmented Lagrangian function; wherein each sub-region is decomposed by the overall regional power system; substituting the tie-line flow of each sub-region as an initial value into the coupling relationship of each corresponding adjacent sub-region to solve the unit combination of each sub-region; and using the ADMM algorithm to calculate the second tie-line flow of each sub-region according to the tie-line flow and unit combination of each sub-region; and performing power system economic scheduling on the overall regional power system according to the unit combination and the second tie-line flow of each sub-region.

Description

Technical Field

[0001] The present invention relates to the technical field of economic dispatch of power systems, and in particular to a multi-region decomposition coordinated optimization dispatching method, device and storage medium. Background Art

[0002] Economic dispatch of power systems aims to meet the load demands of individual user nodes and ensure the security of the power transmission network, rationally arranging unit power generation plans at every moment of every day to minimize the total cost of power generation and transmission. my country's current power system economic dispatch problem is a massive, complex, and systemic challenge. From the perspective of resource distribution, my country's coal, oil, natural gas, and renewable energy resources result in large-scale north-south power consumption and west-east power transmission during power distribution. From the perspective of grid complexity, the interconnection of ultra-high voltage AC and DC lines across provinces and regions is deepening the coupling and increasing the connections between power grids at all levels, providing new opportunities for economic dispatch to further reduce power generation and transmission costs. From the perspective of grid scale, the mathematical models of power generation and consumption nodes and grid lines are enormous, making direct economic dispatch solutions extremely difficult.

[0003] Currently, the economic dispatch of power systems in various provinces and cities often adopts a centralized modeling and direct solution approach. Provincial and municipal power dispatch centers collect relevant information and perform load forecasts for each power-consuming node over multiple periods throughout the day. A mathematical model is then established based on the grid structure, unit status, and node information. The day before power generation, a solver is invoked based on this mathematical model to calculate a multi-period power generation plan for the day, known as the day-ahead power generation plan. Based on the model's solution, the power generation rates of each unit at each time are determined, as well as the power transmission and direction of each line at each moment. Centralized solution models for power system dispatching suffer from the following technical issues: large model size, long solution times, large data volumes, and difficulty in data management and maintenance. Furthermore, centralized solution models fail to account for regional differences. Summary of the Invention

[0004] The present invention provides a multi-region decomposition and coordination optimization scheduling method, device and storage medium to achieve multi-region decomposition and coordination of the overall regional power system, reduce the time for solving the power system economic scheduling plan of the overall power system, and improve the stability of the economic scheduling of the overall region.

[0005] To solve the above technical problems, an embodiment of the present invention provides a multi-region decomposition coordinated optimization scheduling method, comprising performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function for each sub-region; and calculating a first tie-line power flow for each sub-region using an AMMD algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system;

[0006] Substituting the tie-line power flow of each sub-region as an initial value into the corresponding coupling relationship formula of each adjacent sub-region, and solving the unit commitment of each sub-region respectively;

[0007] According to the unit combination of each sub-region and the objective function of each sub-region, the coupling relationship between each adjacent sub-region is relaxed to obtain the second augmented Lagrangian function of each sub-region. According to the second augmented Lagrangian function, the second tie-line flow of each sub-region is calculated using the ADMM algorithm. According to the unit combination of each sub-region and the second tie-line flow, the overall regional power system is economically dispatched.

[0008] As a preferred solution, the present invention divides the entire regional power system into multiple small-scale areas, uses the ADMM algorithm to independently and parallelly solve the tie line flow in each small area, then uses the tie line to exchange information and data between areas, and then solves the unit combination of each sub-area based on the tie line flow solved for each sub-area. Based on the unit combination, the power balance and adjustment of the entire tie line are performed to achieve the economic dispatch of the entire power system. Each sub-area only needs to exchange power information such as power and phase angle through the tie line, and each sub-area can be solved independently. This method reduces the time for solving the overall economic dispatch plan of the power system and takes into account the individual differences of each sub-area. Each sub-area can independently manage and maintain information within its own area, reducing the workload of the power dispatch center and improving the stability of the economic dispatch of the entire area.

[0009] As a preferred solution, each of the sub-regions is decomposed from the overall regional power system, specifically:

[0010] Decomposing the overall regional power system into at least two sub-regions through the transmission mode of equivalent tie lines, taking the tie line transmission power at the boundary connection between adjacent sub-regions as a shared variable, and calculating the coupling relationship between each of the adjacent sub-regions;

[0011] The coupling relationship between area A and area B is expressed as follows:

[0012] T A +T B =0;

[0013] Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas;

[0014] The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region;

[0015] The objective function is:

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g,t,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

[0022] As a preferred solution, the present invention uses the equivalent tie line method, uses tie lines to connect each other, uses the tie line power at the boundary connection between regions as a shared variable, divides the entire area into multiple small-scale areas, and each sub-area independently solves, independently manages and maintains the information within its own area, taking into account the individual differences of each sub-area and reducing the workload of the power dispatching center.

[0023] As a preferred solution, based on the constraints of each sub-region and the objective function of each sub-region, the coupling relationship between each adjacent sub-region is relaxed by augmented Lagrangian to obtain the first augmented Lagrangian function of each sub-region. Based on the first augmented Lagrangian function, the first tie-line power flow of each sub-region is calculated using the AMMD algorithm, specifically:

[0024] performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process;

[0025] The first augmented Lagrangian function of region A and region B is expressed as follows:

[0026]

[0027]

[0028]

[0029] Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A and area B in period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line m in area A and area B in time period t, respectively, and ρ>0 is the coefficient of the quadratic penalty term.

[0030] The first iterative formula is:

[0031]

[0032]

[0033]

[0034] The first original residual ε priand the first pair residual ε dual The expression is:

[0035]

[0036]

[0037] Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size;

[0038] The conventional augmented Lagrangian function is:

[0039] As a preferred solution, the present invention uses the ADMM algorithm to independently solve the tie-line power flows in each subregion, while satisfying the constraints of each subregion. This ADMM algorithm can decompose a large-scale integer problem into several small integer programming problems and simultaneously allow these integer programming problems to be solved in parallel, significantly reducing the complexity of calculating tie-line power flows and shortening the time required to solve them.

[0040] As a preferred solution, based on the unit commitment of each sub-region and the objective function of each sub-region, the coupling relationship between each adjacent sub-region is subjected to augmented Lagrangian relaxation to obtain a second augmented Lagrangian function of each sub-region. Based on the second augmented Lagrangian function, the second tie-line power flow of each sub-region is calculated using the ADMM algorithm, specifically:

[0041] According to the unit commitment of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain the second augmented Lagrangian function of each sub-region. According to the second iterative formula, the second augmented Lagrangian function of each sub-region is iterated. When the second original residual and the second even residual converge during the iterative process, the second tie-line power flow of each sub-region is output.

[0042] As a preferred solution, the present invention reuses the ADMM algorithm to solve the interconnection line flow of each sub-region based on the unit combination of each sub-region, and obtains the optimal interconnection line flow and power system economic dispatch plan for each sub-region. This method of solving the power system economic dispatch plan reduces the time for solving the overall power system economic dispatch plan, allows regions to retain their own privacy information, reduces the amount of data exchange, and at the same time enhances the regional and overall stability of the dispatch.

[0043] Accordingly, the present invention also provides a multi-region decomposition coordination optimization scheduling device, comprising: a multi-region decomposition module and a decomposition coordination optimization scheduling module;

[0044] The multi-region decomposition module is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function of each sub-region, and calculate a first tie-line power flow of each sub-region using an AMMD algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system, and each sub-region satisfies its own constraints;

[0045] The decomposition coordination optimization scheduling module is used to substitute the tie-line flow of each sub-region as an initial value into the corresponding coupling relationship formula of each adjacent sub-region, and solve the unit combination of each sub-region respectively; according to the unit combination of each sub-region and the objective function of each sub-region, the coupling relationship formula between each adjacent sub-region is augmented Lagrangian relaxation to obtain the second augmented Lagrangian function of each sub-region; according to the second augmented Lagrangian function, the second tie-line flow of each sub-region is calculated using the ADMM algorithm, and the overall regional power system is economically dispatched.

[0046] As a preferred solution, the multi-region decomposition coordination optimization scheduling device of the present invention uses a multi-region decomposition module to divide the entire regional power system into multiple small-scale areas. In each small area, the ADMM algorithm is used to independently and parallelly solve the tie line flow. The tie lines are then used to exchange information and data between areas. The unit combination of each sub-area is then solved based on the tie line flow solved for each sub-area. The decomposition coordination optimization scheduling module balances and adjusts the power of the entire tie line based on the unit combination to achieve economic scheduling of the entire power system. Each sub-area only needs to exchange power information such as power and phase angle through the tie lines, and each sub-area can be solved independently. This method reduces the time required to solve the overall economic scheduling plan for the power system and takes into account the individual differences of each sub-area. Each sub-area can independently manage and maintain information within its own area, reducing the workload of the power dispatch center and improving the stability of the overall regional economic scheduling.

[0047] As a preferred solution, the multi-region decomposition module includes a decomposition unit and a tie line power flow calculation unit;

[0048] The decomposition unit is used to decompose the entire regional power system into the sub-regions, specifically:

[0049] Decomposing the overall regional power system into at least two sub-regions through the transmission mode of equivalent tie lines, taking the tie line transmission power at the boundary connection between adjacent sub-regions as a shared variable, and calculating the coupling relationship between each of the adjacent sub-regions;

[0050] The coupling relationship between area A and area B is expressed as follows:

[0051] T A +T B =0;

[0052] Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas;

[0053] The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region;

[0054] The objective function is:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060] Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g,t,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

[0061] The tie-line power flow calculation unit is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the objective function of each sub-region, obtain a first augmented Lagrangian function of each sub-region, and calculate the first tie-line power flow of each sub-region using the AMMD algorithm based on the first augmented Lagrangian function, specifically:

[0062] performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process;

[0063] The first augmented Lagrangian function of region A and region B is expressed as follows:

[0064]

[0065]

[0066]

[0067] Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A and area B in period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line m in area A and area B in time period t, respectively, and ρ>0 is the coefficient of the quadratic penalty term.

[0068] The first iterative formula is:

[0069]

[0070]

[0071]

[0072] The first original residual ε pri and the first pair residual ε dual The expression is:

[0073]

[0074]

[0075] Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size;

[0076] The conventional augmented Lagrangian function is:

[0077] As a preferred solution, the decomposition units of the multi-region decomposition module of the multi-region decomposition coordination optimization scheduling device of the present invention use the equivalent interconnection line method, use interconnection lines to connect each other, use the interconnection line power at the boundary connection between regions as a shared variable, divide the entire region into multiple small-scale regions, and each sub-region independently solves, independently manages and maintains the information within its own region, taking into account the individual differences of each sub-region and reducing the workload of the power dispatching center.

[0078] The tie-line power flow calculation unit uses the ADMM algorithm to independently solve the tie-line power flow in each sub-area, while satisfying the constraints of each sub-area. This ADMM algorithm can decompose a large-scale integer problem into several small integer programming problems and allow these integer programming problems to be solved in parallel, significantly reducing the complexity of calculating tie-line power flows and shortening the time required to solve them.

[0079] As a preferred solution, the decomposition coordination optimization scheduling module includes: unit commitment calculation unit and economic scheduling calculation unit;

[0080] The unit commitment calculation unit is used to substitute the tie-line power flow of each sub-region as an initial value into the coupling relationship formula of each corresponding adjacent sub-region, and solve the unit commitment of each sub-region respectively;

[0081] The economic dispatch calculation unit is used to perform augmented Lagrangian relaxation on the coupling relationship between each adjacent sub-region based on the unit combination of each sub-region and the objective function of each sub-region, obtain the second augmented Lagrangian function of each sub-region, iterate the second augmented Lagrangian function of each sub-region according to the second iterative formula, and when the second original residual and the second even residual converge during the iterative process, output the second tie-line flow of each sub-region, and perform power system economic dispatch on the overall regional power system based on the unit combination and the second tie-line flow of each sub-region.

[0082] As a preferred solution, the economic dispatch calculation unit of the decomposition and coordination optimization dispatch module of the multi-region decomposition and coordination optimization dispatch device of the present invention reuses the ADMM algorithm to solve the interconnection line flow of each sub-region according to the unit combination of each sub-region, and obtains the optimal interconnection line flow and power system economic dispatch plan for each sub-region. This method of solving the power system economic dispatch plan reduces the time for solving the overall power system economic dispatch plan, allows regions to retain their own privacy information, reduces the amount of data exchange, and at the same time enhances the regional and overall stability of the dispatch.

[0083] Accordingly, the present invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute a multi-area decomposition coordination optimization scheduling method as described in the content of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 This is a flow chart of an embodiment of the multi-region decomposition coordination optimization scheduling method provided by the present invention;

[0085] Figure 2 It is a structural diagram of an embodiment of the multi-region decomposition coordination optimization scheduling device provided by the present invention. DETAILED DESCRIPTION

[0086] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0087] Example 1

[0088] Please refer to Figure 1 , a multi-region decomposition coordination optimization scheduling method provided by an embodiment of the present invention includes steps S101-S103:

[0089] Step S101: performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function of each sub-region; and calculating a first tie-line power flow of each sub-region using the AMMD algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system;

[0090] In this embodiment, each of the sub-regions is decomposed from the overall regional power system, specifically:

[0091] Decomposing the overall regional power system into at least two sub-regions through the transmission mode of equivalent tie lines, taking the tie line transmission power at the boundary connection between adjacent sub-regions as a shared variable, and calculating the coupling relationship between each of the adjacent sub-regions;

[0092] The coupling relationship between area A and area B is expressed as follows:

[0093] T A +T B =0;

[0094] Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas;

[0095] The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region;

[0096] The objective function is:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g, t ,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

[0103] In this embodiment, based on the constraints of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain the first augmented Lagrangian function of each sub-region. Based on the first augmented Lagrangian function, the first tie-line power flow of each sub-region is calculated using the AMMD algorithm, specifically:

[0104] performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process;

[0105] The first augmented Lagrangian function of region A and region B is expressed as follows:

[0106]

[0107]

[0108]

[0109] Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A and area B in period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line m in area A and area B in time period t, respectively, and ρ>0 is the coefficient of the quadratic penalty term.

[0110] The first iterative formula is:

[0111]

[0112]

[0113]

[0114] The first original residual ε pri and the first pair residual ε dual The expression is:

[0115]

[0116]

[0117] Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size;

[0118] The conventional augmented Lagrangian function is:

[0119] In this embodiment, the constraints of each sub-area include: upper and lower limits of unit output, coupling constraints of unit start-stop status and start-stop action, unit ramping constraints, minimum continuous start-stop time constraints, node power balance constraints, line power flow constraints, and tie-line power flow constraints;

[0120] The upper and lower limits of the unit output are:

[0121]

[0122] Where a g,t Indicates the start and stop status of the unit during time period t; The upper and lower limits of the unit output;

[0123] The coupling constraints between the start-stop state and the start-stop action of the unit are:

[0124]

[0125] Where, γ g,t Indicates whether the unit has switched to the shutdown state;

[0126] The unit climbing constraint is:

[0127]

[0128]

[0129] Where, are the maximum ramp-up rate and maximum ramp-down rate of thermal power units respectively;

[0130] The shortest continuous start-up and shutdown time constraint of the unit is:

[0131]

[0132]

[0133] Where: are the minimum continuous start-up and shutdown time of thermal power units respectively; are the time that the thermal power unit has been continuously started and stopped at time t;

[0134] The maximum number of start and stop times of the unit is constrained as follows:

[0135]

[0136]

[0137] Where: are the maximum number of starts and stops of thermal power units respectively;

[0138] The node power balance constraint is:

[0139]

[0140] Where: Ω G,i is the set of units at node i; Ω i- ,Ω i+ are the branches flowing out and into node i respectively; Ω T,i- is the set of tie lines flowing out of node i; F l,t is the active power flow of line l in period t; D i,t is the load demand curve of node i; T m,t is the active power flow of tie line m in period t;

[0141] The line power flow constraint is:

[0142] F l,t -B l (θ Bgn,l,t -θ End,l,t )=0;

[0143] -F l max ≤F l,t ≤F l max ;

[0144] Where: B l is the susceptance of line l; θ Bgn,l,t ,θ End,l,t are the phase angles of the first and last nodes of line l in time period t; F l max is the upper limit of active power flow transmission of line l;

[0145] The tie line power flow constraint is:

[0146]

[0147] Where: is the upper limit of active power flow transmission of tie line m.

[0148] Step S102: Substituting the tie-line power flow of each sub-region as an initial value into the corresponding coupling relationship formula of each adjacent sub-region, and solving the unit commitment of each sub-region respectively;

[0149] In this embodiment, the tie line flow of each sub-area is used as the initial value T A(0) ,T B(0) , substitute the corresponding coupling relationship T of each adjacent sub-region A +T B = 0, solve the unit combination of each sub-area respectively.

[0150] Step S103: Based on the unit combination of each sub-region and the objective function of each sub-region, perform augmented Lagrangian relaxation on the coupling relationship between each adjacent sub-region to obtain the second augmented Lagrangian function of each sub-region; based on the second augmented Lagrangian function, use the ADMM algorithm to calculate the second tie-line flow of each sub-region; based on the unit combination of each sub-region and the second tie-line flow, perform power system economic dispatch on the overall regional power system.

[0151] In this embodiment, based on the unit commitment of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain a second augmented Lagrangian function of each sub-region. Based on the second augmented Lagrangian function, the second tie-line power flow of each sub-region is calculated using the ADMM algorithm, specifically:

[0152] According to the unit commitment of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain the second augmented Lagrangian function of each sub-region. According to the second iterative formula, the second augmented Lagrangian function of each sub-region is iterated. When the second original residual and the second even residual converge during the iterative process, the second tie-line power flow of each sub-region is output.

[0153] In this embodiment, the objective function of each sub-region is:

[0154]

[0155]

[0156]

[0157]

[0158]

[0159] Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g, t ,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

[0160] In this embodiment, the second augmented Lagrangian function of region A and region B is expressed as follows:

[0161]

[0162]

[0163]

[0164] Where, are the second augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A and area B in period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line m in area A and area B in time period t, respectively, and ρ>0 is the coefficient of the quadratic penalty term.

[0165] The second iteration formula is:

[0166]

[0167]

[0168]

[0169] The second original residual ε pri and the second dual residual ε dual The expression is:

[0170]

[0171]

[0172] Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size.

[0173] The implementation of the present invention has the following effects:

[0174] The present invention divides the entire regional power system into multiple small-scale areas, uses the ADMM algorithm to independently and parallelly solve the tie-line flow in each small area, then uses the tie-line to exchange information and data between areas, and then solves the unit combination of each sub-area based on the tie-line flow solved for each sub-area. Based on the unit combination, the overall tie-line is power balanced and adjusted to achieve the overall economic dispatch of the power system. Each sub-area only needs to exchange power information such as power and phase angle through the tie-line, and each sub-area can be solved independently. This method reduces the time required to solve the overall economic dispatch plan of the power system and takes into account the individual differences of each sub-area. Each sub-area can independently manage and maintain information within its own area, reducing the workload of the power dispatch center and improving the stability of the overall regional economic dispatch.

[0175] Example 2

[0176] Please refer to Figure 2 , a multi-region decomposition coordination optimization scheduling device provided by an embodiment of the present invention includes: a multi-region decomposition module 201 and a decomposition coordination optimization scheduling module 202;

[0177] The multi-region decomposition module 201 is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function of each sub-region, and calculate a first tie-line power flow of each sub-region using the AMMD algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system, and each sub-region satisfies its own constraints;

[0178] The decomposition coordination optimization scheduling module 201 is used to substitute the tie-line flow of each sub-region as an initial value into the corresponding coupling relationship formula of each adjacent sub-region, and solve the unit combination of each sub-region respectively; according to the unit combination of each sub-region and the objective function of each sub-region, the coupling relationship formula between each adjacent sub-region is augmented Lagrangian relaxation to obtain the second augmented Lagrangian function of each sub-region; according to the second augmented Lagrangian function, the second tie-line flow of each sub-region is calculated using the ADMM algorithm, and the overall regional power system is economically dispatched.

[0179] The multi-region decomposition module includes a decomposition unit and a tie line power flow calculation unit;

[0180] The decomposition unit is used to decompose the entire regional power system into the sub-regions, specifically:

[0181] Decomposing the overall regional power system into at least two sub-regions through the transmission mode of equivalent tie lines, taking the tie line transmission power at the boundary connection between adjacent sub-regions as a shared variable, and calculating the coupling relationship between each of the adjacent sub-regions;

[0182] The coupling relationship between area A and area B is expressed as follows:

[0183] T A +T B =0;

[0184] Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas;

[0185] The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region;

[0186] The objective function is:

[0187]

[0188]

[0189]

[0190]

[0191]

[0192] Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g,t,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

[0193] The tie-line power flow calculation unit is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the objective function of each sub-region, obtain a first augmented Lagrangian function of each sub-region, and calculate the first tie-line power flow of each sub-region using the AMMD algorithm based on the first augmented Lagrangian function, specifically:

[0194] performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process;

[0195] The first augmented Lagrangian function of region A and region B is expressed as follows:

[0196]

[0197]

[0198]

[0199] Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A and area B in period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line m in area A and area B in time period t, respectively, and ρ>0 is the coefficient of the quadratic penalty term.

[0200] The first iterative formula is:

[0201]

[0202]

[0203]

[0204] The first original residual ε pri and the first pair residual ε dual The expression is:

[0205]

[0206]

[0207] Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size;

[0208] The conventional augmented Lagrangian function is:

[0209] The decomposition coordination optimization scheduling module includes: a unit combination calculation unit and an economic scheduling calculation unit;

[0210] The unit commitment calculation unit is used to substitute the tie-line power flow of each sub-region as an initial value into the coupling relationship formula of each corresponding adjacent sub-region, and solve the unit commitment of each sub-region respectively;

[0211] The economic dispatch calculation unit is used to perform augmented Lagrangian relaxation on the coupling relationship between each adjacent sub-region based on the unit combination of each sub-region and the objective function of each sub-region, obtain the second augmented Lagrangian function of each sub-region, iterate the second augmented Lagrangian function of each sub-region according to the second iterative formula, and when the second original residual and the second even residual converge during the iterative process, output the second tie-line flow of each sub-region, and perform power system economic dispatch on the overall regional power system based on the unit combination and the second tie-line flow of each sub-region.

[0212] The multi-region decomposition, coordination, and optimization scheduling device described above can implement the multi-region decomposition, coordination, and optimization scheduling method of the aforementioned method embodiment. The optional options in the aforementioned method embodiment also apply to this embodiment and will not be described in detail here. The remaining contents of the embodiments of this application can be referenced to the contents of the aforementioned method embodiment and will not be further described in this embodiment.

[0213] The implementation of the present invention has the following effects:

[0214] The multi-region decomposition, coordination and optimization scheduling device of the present invention uses a multi-region decomposition module to divide the entire regional power system into multiple small-scale regions. In each small region, the ADMM algorithm is used to independently and parallelly solve the tie line flow. The tie lines are then used to exchange information and data between regions. The unit combination of each sub-region is then solved based on the tie line flow solved for each sub-region. The decomposition, coordination and optimization scheduling module performs power balance and adjustment on the entire tie line based on the unit combination to achieve economic scheduling of the entire power system. Each sub-region only needs to exchange power information such as power and phase angle through the tie lines, and each sub-region can independently solve the problem. This method reduces the time required to solve the overall economic scheduling plan for the power system and takes into account the individual differences of each sub-region. Each sub-region can independently manage and maintain information within its own region, reducing the workload of the power dispatch center and improving the stability of the overall regional economic scheduling.

[0215] Example 3

[0216] Accordingly, the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the multi-area decomposition coordination optimization scheduling method described in any one of the above embodiments.

[0217] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0218] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0219] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0220] The memory can be used to store the computer programs and / or modules. The processor realizes various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile terminal, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0221] Wherein, if the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0222] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A multi-region decomposition coordination optimization scheduling method, characterized in that: include: performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function of each sub-region; and calculating a first tie-line power flow of each sub-region using an ADMM algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system; Substituting the tie-line power flow of each sub-region as an initial value into the corresponding coupling relationship formula of each adjacent sub-region, and solving the unit commitment of each sub-region respectively; performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the unit commitment of each sub-region and the objective function of each sub-region to obtain a second augmented Lagrangian function of each sub-region; calculating a second tie-line flow of each sub-region using an ADMM algorithm based on the second augmented Lagrangian function; and performing power system economic dispatch on the overall regional power system based on the unit commitment of each sub-region and the second tie-line flow. The sub-regions are decomposed from the overall regional power system, specifically by: decomposing the overall regional power system into at least two sub-regions through the transmission mode of equivalent tie lines, taking the tie line transmission power at the boundary connection between adjacent sub-regions as a shared variable, and calculating the coupling relationship between each of the adjacent sub-regions; The coupling relationship between area A and area B is expressed as follows: T A +T B =0; Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas; The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region; The objective function is: Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g,t,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

2. The multi-region decomposition coordination optimization scheduling method according to claim 1, characterized in that: According to the constraints of each sub-region and the objective function of each sub-region, the coupling relationship between each adjacent sub-region is relaxed by augmented Lagrangian to obtain the first augmented Lagrangian function of each sub-region. According to the first augmented Lagrangian function, the first tie-line power flow of each sub-region is calculated using the ADMM algorithm, specifically: performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process; The first augmented Lagrangian function of region A and region B is expressed as follows: Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A during period t, are the operating cost and startup cost of unit g in area B during period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line n in area A and area B in time period t, ρ>0 is the coefficient of the quadratic penalty term; The first iterative formula is: The first original residual ε pri and the first pair residual ε dual The expression is: Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size; The conventional augmented Lagrangian function is:

3. The multi-region decomposition coordination optimization scheduling method according to claim 1, characterized in that: According to the unit commitment of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain a second augmented Lagrangian function of each sub-region. According to the second augmented Lagrangian function, the second tie-line power flow of each sub-region is calculated using the ADMM algorithm, specifically: According to the unit commitment of each sub-region and the objective function of each sub-region, augmented Lagrangian relaxation is performed on the coupling relationship between each adjacent sub-region to obtain the second augmented Lagrangian function of each sub-region. According to the second iterative formula, the second augmented Lagrangian function of each sub-region is iterated. When the second original residual and the second even residual converge during the iterative process, the second tie-line power flow of each sub-region is output.

4. A multi-region decomposition coordination optimization scheduling device, characterized in that: include: Multi-region decomposition module and decomposition coordination optimization scheduling module; The multi-region decomposition module is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions based on the constraints of each sub-region and the objective function of each sub-region to obtain a first augmented Lagrangian function of each sub-region, and calculate a first tie-line power flow of each sub-region using an ADMM algorithm based on the first augmented Lagrangian function; wherein each sub-region is decomposed from the overall regional power system, and each sub-region satisfies its own constraints; The decomposition coordination optimization scheduling module is used to substitute the tie-line flow of each sub-region as an initial value into the coupling relationship formula of each corresponding adjacent sub-region, and solve the unit commitment of each sub-region respectively; according to the unit commitment of each sub-region and the objective function of each sub-region, perform augmented Lagrangian relaxation on the coupling relationship formula between each adjacent sub-region to obtain the second augmented Lagrangian function of each sub-region; according to the second augmented Lagrangian function, use the ADMM algorithm to calculate the second tie-line flow of each sub-region; according to the unit commitment of each sub-region and the second tie-line flow, perform power system economic scheduling on the overall regional power system; The multi-region decomposition module includes a decomposition unit, which is used to decompose the overall regional power system into each of the sub-regions. Specifically, the overall regional power system is decomposed into at least two sub-regions through the transmission mode of equivalent tie lines, and the tie line transmission power at the boundary connection between adjacent sub-regions is used as a shared variable to calculate the coupling relationship between each of the adjacent sub-regions. The coupling relationship between area A and area B is expressed as follows: T A +T B =0; Where, T A 、T B are the transmission power of the boundary tie line of area A relative to area B, and the transmission power of the boundary tie line of area B relative to area A, respectively. The area A and the area B are two adjacent sub-areas; The objective function corresponding to each sub-region is constructed by minimizing the total system power generation cost of each sub-region; The objective function is: Where, T is the total number of time periods; N G is the total number of units; C g,t (P g,t ), is the operating cost and startup cost of unit g in period t, where C g,t (P g,t ) is a multi-segment linear function related to the unit output; P g,t is the output of unit g in period t; N M P is the total number of sections in the unit quotation; g,t,m is the winning bid power of unit g in the mth output interval in time period t; are the maximum and minimum values ​​of unit g in the mth output interval respectively; c g,t,m is the unit power generation cost corresponding to the mth output interval declared by unit g in time period t; is the startup cost of unit g; η g,t Indicates whether unit g is switched to the start state during time period t.

5. The multi-region decomposition coordination optimization scheduling device according to claim 4, characterized in that: The multi-region decomposition module also includes a tie line power flow calculation unit; The tie-line power flow calculation unit is configured to perform augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the objective function of each sub-region, obtain a first augmented Lagrangian function of each sub-region, and calculate the first tie-line power flow of each sub-region using the ADMM algorithm based on the first augmented Lagrangian function, specifically: performing augmented Lagrangian relaxation on the coupling relationship between adjacent sub-regions according to the constraints of each sub-region, substituting the objective function of each sub-region into the augmented Lagrangian function to obtain the first augmented Lagrangian function of each sub-region, iterating the first augmented Lagrangian function of each sub-region according to the first iterative formula, and outputting the first tie-line power flow of each sub-region when the first original residual and the first even residual converge during the iterative process; The first augmented Lagrangian function of region A and region B is expressed as follows: Where, are the first augmented Lagrangian functions of region A and region B respectively; T is the total number of time periods; are the total number of units in Area A and Area B respectively; are the operating cost and startup cost of unit g in area A during period t, are the operating cost and startup cost of unit g in area B during period t, respectively, where are multi-segment linear functions related to the unit output in area A and area B respectively; It is the set of connecting lines between area A and area B and the flow from A to B; is the set of connecting lines between area B and area A and where B flows to A; the area A and the area B are two adjacent sub-areas; are the active power flows of tie line n in area A and area B in time period t, ρ>0 is the coefficient of the quadratic penalty term; The first iterative formula is: The first original residual ε pri and the first pair residual ε dual The expression is: Where x1, x2, A1, A2, b and ρ are the parameters of the conventional augmented Lagrangian function, y is the Lagrangian multiplier, and y k is the parameter of the conventional augmented Lagrangian function after k iterations, and y k+1 is the parameter of the conventional augmented Lagrangian function after (k+1) iterations, and τ is the step size; The conventional augmented Lagrangian function is:

6. The multi-region decomposition coordination optimization scheduling device according to claim 4, characterized in that: The decomposition coordination optimization scheduling module includes: a unit combination calculation unit and an economic scheduling calculation unit; The unit commitment calculation unit is used to substitute the tie-line power flow of each sub-region as an initial value into the coupling relationship formula of each corresponding adjacent sub-region, and solve the unit commitment of each sub-region respectively; The economic dispatch calculation unit is used to perform augmented Lagrangian relaxation on the coupling relationship between each adjacent sub-region based on the unit combination of each sub-region and the objective function of each sub-region, obtain the second augmented Lagrangian function of each sub-region, iterate the second augmented Lagrangian function of each sub-region according to the second iterative formula, and when the second original residual and the second even residual converge during the iterative process, output the second tie-line flow of each sub-region, and perform power system economic dispatch on the overall regional power system based on the unit combination and the second tie-line flow of each sub-region.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program; wherein, when the computer program is run, it controls the device where the computer-readable storage medium is located to execute a multi-area decomposition coordination optimization scheduling method according to any one of claims 1 to 3.

Images