Trans-provincial green electricity optimal scheduling method considering AC / DC tie line constraint

Abstract

The invention relates to a trans-provincial green electricity optimal scheduling method considering AC / DC tie line constraint, and belongs to the technical field of power planning. The method comprises the following steps: constructing an inter-provincial first-level optimization scheduling cost model based on output of each conventional unit and each new energy unit in a scheduling range, and conventional energy power and new energy power transmitted by each trans-provincial tie line; constructing an intra-province secondary optimization scheduling cost model based on the output of each conventional unit and the output of each new energy unit in each province; with the minimum first-level scheduling cost as the target, the transmission power of the inter-provincial tie line is solved based on set constraints and serves as an inter-provincial scheduling scheme; and solving based on the transmission power of the inter-province tie line and the set constraint by taking the minimum in-province secondary optimization scheduling cost as a target to obtain an in-province unit output scheduling scheme of each province region. According to the method, the alternating current and direct current tie line constraint of trans-provincial dispatching is considered, and the secondary optimization model is constructed, so that the system power generation cost can be reduced, and the inter-provincial and intra-provincial new energy consumption can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power planning, and in particular relates to a method for optimizing green power dispatching across provinces and regions taking into account constraints of AC and DC interconnection lines. Background Art

[0002] As environmental problems become increasingly serious, countries around the world have stepped up the development and utilization of renewable energy. Green electricity energy, mainly wind power, photovoltaic power, and hydropower, has become an important form of power energy supply, providing favorable energy support for the power system. However, due to its natural volatility and intermittency, the power generation output of green electricity is highly uncertain in both time and space, posing challenges to the stability and economy of the power grid. Among them, wind power, photovoltaic power and other new energy power generation, due to the characteristics of geographical distribution, are limited by the transmission capacity of the power grid, the rationality of the power system scheduling, and the fluctuations in the needs of power grid users, and there are serious energy wastes such as wind and light abandonment. Therefore, how to make full use of existing power transmission lines, rationally optimize the scheduling of green electricity across provinces and regions, improve the utilization rate of new energy, and reduce the power supply cost of the power system is an urgent problem to be solved. Summary of the invention

[0003] In view of the above analysis, the present invention aims to provide a cross-provincial optimization scheduling method taking into account the constraints of AC and DC interconnection lines. By considering the constraints of AC and DC interconnection lines in cross-provincial scheduling and constructing a two-level green electricity optimization scheduling model between provinces and within provinces, the green electricity scheduling plans between provinces and within provinces are solved, which can effectively reduce the power generation cost of the power system and improve the consumption of new energy.

[0004] The present invention provides a method for optimizing the dispatch of green electricity across provinces and regions taking into account the constraints of AC and DC interconnection lines, which specifically includes the following steps:

[0005] Based on the output of each conventional unit, the output of each new energy unit, the conventional energy power transmitted by each inter-provincial interconnection line, and the new energy power transmitted by each inter-provincial interconnection line within the scope of inter-provincial dispatch, a provincial first-level optimization dispatch cost model is constructed;

[0006] Based on the output of each conventional unit and each new energy unit in each province, a provincial secondary optimization dispatch cost model is constructed;

[0007] With the goal of minimizing the inter-provincial first-level optimization dispatching cost, the inter-provincial first-level optimization dispatching cost model is solved based on the regional power balance constraints, regional new energy consumption responsibility constraints, cross-regional and cross-provincial interconnection line constraints, thermal power unit constraints, and new energy medium- and long-term supply constraints to obtain the conventional energy power transmitted by each interconnection line and the new energy power transmitted by each interconnection line;

[0008] With the goal of minimizing the cost of the provincial secondary optimization dispatching, the provincial secondary optimization dispatching cost model of each province is solved based on the conventional energy power transmitted by each of the interconnection lines, the new energy power transmitted by each of the interconnection lines, and the line flow constraints and section flow constraints, and the output of each conventional unit and each new energy unit in each province is obtained.

[0009] Furthermore, the inter-provincial first-level optimization dispatch cost model is constructed based on the output of each conventional unit, the output of each new energy unit, the conventional energy power transmitted by each inter-provincial interconnection line, and the new energy power transmitted by each inter-provincial interconnection line within the scope of inter-provincial dispatch, including:

[0010] Constructing a power generation cost model based on the output of each conventional unit and the output of each new energy unit;

[0011] Constructing a carbon emission cost model based on the output of each conventional unit;

[0012] Constructing a tie line transmission cost model based on the conventional energy power transmitted by each tie line and the new energy power transmitted by each tie line;

[0013] Constructing a network loss cost model based on the network loss of each of the tie lines;

[0014] Construct an excess consumption purchase cost model based on the excess consumption of each province and region;

[0015] A first-level inter-provincial optimization dispatching cost model is constructed based on the power generation cost model, carbon emission cost model, interconnection line transmission cost model, network loss cost model and excess consumption purchase cost model.

[0016] Furthermore, based on the output of each conventional unit and each new energy unit in each province, a provincial secondary optimization dispatch cost model is constructed for each province, including:

[0017] Construct the power generation cost model for each province based on the output of each conventional unit and each new energy unit in each province;

[0018] Based on the output of each conventional unit in each province, a carbon emission cost model for each province is constructed;

[0019] Based on the excess consumption of each province and region, a purchase cost model for excess consumption of each province and region is constructed;

[0020] Based on the power generation cost model of each province and region, the carbon emission cost model of each province and region, and the excess consumption purchase cost model of each province and region, a provincial secondary optimization scheduling cost model is constructed for each province and region.

[0021] Furthermore, the inter-regional and inter-provincial tie line constraints include DC tie line constraints and AC tie line constraints; the DC tie line constraints include DC tie line transmission power constraints, DC tie line transmission power ramp constraints and DC tie line network loss constraints, which are respectively expressed as:

[0022]

[0023] in, and They represent the transmission power, minimum transmission power and maximum transmission power of the DC tie line l in period t respectively; and 0 / 1 variables representing up and down power respectively; Indicates the minimum climbing transmission power of the transmission line; Indicates the minimum climbing transmission power of the transmission line; Represents the linear proportionality coefficient of the network loss of the DC tie line l.

[0024] Furthermore, the AC tie line constraint includes an AC tie line transmission power constraint and an AC tie line network loss constraint, which are respectively expressed as:

[0025]

[0026] in, and They represent the transmission power, minimum transmission power and maximum transmission power of the AC tie line l in time period t; R represents the number of provinces; N r represents the total number of generating units in province r, including conventional generating units and new energy generating units; G i-l represents the power transfer distribution factor of the generator set in province r to the AC tie line; P i,r,t N represents the power generation of generator set i in province r during period t; dc represents the set of inter-provincial DC interconnection lines; G d-a It represents the power transfer distribution factor of the DC tie line to the AC tie line; G represents the transmission power of DC tie line l in period t; j-l N represents the power transfer distribution factor of the load in province r to the AC tie line; Dr represents the total number of loads in province r; D j,r,t represents the load forecast value of province r in period t; Represents the linear proportional coefficient of the network loss of the AC tie line l.

[0027] Furthermore, the inter-provincial level optimization scheduling cost model is expressed as:

[0028]

[0029] Among them, C1, C gen , C car , C tra , C was , C tgc They represent the inter-provincial first-level optimization dispatching cost, power generation cost, carbon emission cost, interconnection line transmission cost, network loss cost and excess consumption purchase cost respectively;

[0030] represents the total electricity cost of conventional generator sets; represents the total electricity cost of the new energy unit; T represents the total number of time periods; N Er and N GEr They represent the number of conventional generating units and the number of new energy generating units that provide electricity to province r; K represents the total number of segments of the quotation; represents the power output of conventional unit i in the kth segment of time period t; α i,k,r,t represents the declared price of the electric energy of the conventional unit i in the kth period of time t; represents the output of the new energy unit m in the kth segment of time period t; γ m,k,r,t It represents the price quoted by the new energy unit m in the kth period of time period t; is the startup cost of conventional unit i in period t;

[0031] is the carbon emission intensity of conventional generator set i; represents the benchmark carbon emission intensity corresponding to conventional power generation unit i; β c represents the carbon price;

[0032] represents the transmission price of the lth inter-provincial tie line; L represents the total number of regional tie lines; and They represent the conventional energy and new energy power transmitted by the lth inter-provincial interconnection line in time period t respectively;

[0033] N dc and N ac They represent the collection of DC interconnection lines and AC interconnection lines between provinces respectively; C L,l represents the network loss penalty factor of tie line l; and Indicates the network loss of AC tie line, DC tie line and DC tie line;

[0034] C tgcc is the national excess consumption price; P tgc It is the excess consumption amount.

[0035] Furthermore, the provincial secondary optimization scheduling cost model is expressed as:

[0036]

[0037] Among them, C2, They represent the provincial secondary optimization dispatch cost, provincial power generation cost, provincial carbon emission cost, and provincial excess consumption purchase cost of province r respectively;

[0038] represents the total electricity cost of conventional generators in province r; Represents the total electricity cost of new energy units in province r.

[0039] Furthermore, the partition power balance constraint includes a regional power balance constraint, a regional positive spare capacity constraint and a regional negative spare capacity constraint, which are respectively expressed as:

[0040]

[0041] in, and They represent the total winning bid output of conventional unit i and new energy unit m in province r during period t; N Tr represents the set of contact lines associated with province r; and They represent the conventional energy and new energy power injected into the tie line l in province r during period t, respectively. Positive numbers represent the power flowing into province r. D j,r,t represents the load forecast value of province r in period t;

[0042] represents the maximum output of generator set i in province r during time period t; z i,t represents the start and stop status of generator set i in province r during period t; represents the positive reserve capacity demand corresponding to province r; T l,t represents the transmission power of the transmission line l connected to province r in time period t;

[0043] represents the minimum output of generator set i in province r during time period t; It represents the negative spare capacity demand corresponding to province r.

[0044] Furthermore, the new energy consumption responsibility constraint is expressed as:

[0045]

[0046] in, represents the excess consumption of province r; μ is the new energy consumption responsibility weight of province r; It represents the tradable excess consumption in province r.

[0047] Furthermore, the line power flow constraint and section power flow constraint are respectively expressed as:

[0048]

[0049] Among them, G i-b represents the power transfer distribution factor of the generator set i to the line in province r, G l-b represents the power transfer distribution factor of the tie line l to the line, G j-b represents the power transfer distribution factor of the generator set i to the line in province r; represents the maximum transmission power of the bth transmission line in province r; T l,t represents the transmission power of the transmission line l connected to province r;

[0050] represents the maximum transmission power of section s within province r; G i-5 G represents the power transfer distribution factor of the section flow of the generator set i in the province r; l-s G represents the power transfer distribution factor of the tie line l to the cross-section flow; j-s It represents the power transfer distribution factor of generator i to the section flow in province t.

[0051] The present invention can achieve at least one of the following beneficial effects:

[0052] By considering the constraints of AC and DC interconnection lines for cross-provincial dispatching and constructing a first-level inter-provincial optimization dispatching cost model and a second-level intra-provincial optimization dispatching cost model, the transmission power of inter-provincial and cross-regional interconnection lines and the dispatching plans for each unit in each province are obtained step by step, effectively reducing the power generation cost of the power system and improving the absorption of new energy.

[0053] By constructing DC interconnection line constraints and AC interconnection line constraints, the transmission power limitation and network loss are taken into consideration to accurately model inter-provincial scheduling; by constructing line flow constraints and section flow constraints, the transmission of intra-provincial lines is accurately modeled to improve the accuracy and scientificity of solving scheduling solutions.

[0054] Other features and advantages of the present invention will be described in the following description, and some advantages may become apparent from the description, or may be understood by practicing the present invention. The purpose and other advantages of the present invention may be realized and obtained through the contents particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. In the entire drawings, the same reference symbols represent the same components;

[0056] Figure 1This is a flow chart of the optimization scheduling method of the present invention. DETAILED DESCRIPTION

[0057] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0058] A specific embodiment of the present invention discloses a method for optimizing green power dispatch across provinces and regions taking into account AC and DC interconnection line constraints, which specifically includes the following steps:

[0059] Step S01, constructing an inter-provincial first-level optimization dispatching cost model based on the output of each conventional unit, the output of each new energy unit, the conventional energy power transmitted by each inter-provincial interconnection line, and the new energy power transmitted by each inter-provincial interconnection line within the scope of inter-provincial dispatching;

[0060] Step S02: constructing a provincial secondary optimization dispatch cost model for each province based on the output of each conventional unit and each new energy unit in each province;

[0061] Step S03, with the goal of minimizing the inter-provincial first-level optimization dispatching cost, solving the inter-provincial first-level optimization dispatching cost model based on the regional power balance constraint, regional new energy consumption responsibility constraint, cross-regional and cross-provincial interconnection line constraint, thermal power unit constraint, and new energy medium- and long-term supply constraint, to obtain the conventional energy power transmitted by each interconnection line and the new energy power transmitted by each interconnection line;

[0062] Step S04, with the goal of minimizing the provincial secondary optimization dispatching cost, the provincial secondary optimization dispatching cost model of each province is solved based on the conventional energy power transmitted by each of the interconnection lines, the new energy power transmitted by each of the interconnection lines, and the line flow constraints and section flow constraints to obtain the output of each conventional unit and each new energy unit in each province.

[0063] In this embodiment, by considering the constraints of AC and DC interconnection lines for cross-provincial scheduling and constructing a first-level inter-provincial optimization scheduling cost model and a second-level intra-provincial optimization scheduling cost model, the transmission power of inter-provincial and cross-regional interconnection lines and the scheduling plan of each unit in each province are solved step by step, thereby effectively reducing the power generation cost of the power system and improving the absorption of new energy.

[0064] It should be noted that green electricity in the present invention mainly discusses new energy units, so the green electricity optimization scheduling of the method of the present invention refers to the scheduling optimization of new energy electricity. The conventional units in the present invention refer to power generation units that use traditional energy to generate electricity, such as coal, natural gas, etc.

[0065] Specifically, in the present invention, the scope of cross-provincial scheduling needs to include multiple provinces (or autonomous regions), and the cross-regional and cross-provincial connection lines include transmission connection lines between each other within the cross-provincial scheduling scope (within the region).

[0066] Specifically, in one embodiment of the present invention, step S01 includes:

[0067] Constructing a power generation cost model based on the output of each conventional unit and each new energy unit within the said range;

[0068] Constructing a carbon emission cost model based on the output of each conventional unit;

[0069] Constructing a tie line transmission cost model based on the conventional energy power transmitted by each tie line and the new energy power transmitted by each tie line;

[0070] Constructing a network loss cost model based on the network loss of each of the tie lines;

[0071] Construct a cost model for purchasing excess consumption within the scope of the above-mentioned scope based on the excess consumption of each province and region;

[0072] A first-level inter-provincial optimization dispatching cost model is constructed based on the power generation cost model, carbon emission cost model, interconnection line transmission cost model, network loss cost model and excess consumption purchase cost model.

[0073] Furthermore, the inter-provincial level optimization dispatch cost model is expressed as:

[0074]

[0075] Among them, C1, C gen , C car , C tra , C was , C tgc They represent the inter-provincial first-level optimization dispatching cost, power generation cost, carbon emission cost, interconnection line transmission cost, network loss cost and excess consumption purchase cost respectively;

[0076] represents the total electricity cost of conventional generator sets; represents the total electricity cost of the new energy unit; R represents the number of provinces and regions; T represents the total number of time periods; N Er and N GEr They represent the number of conventional generating units and new energy generating units that provide electricity to province r, including point-to-grid generating units that are not located in province r; K represents the total number of segments of the quotation; represents the power output of conventional unit i in the kth segment of time period t; α i,k,r,t represents the declared price of the electric energy of the conventional unit i in the kth period of time t; represents the output of the new energy unit m in the kth segment of time period t; γ m,k,r,t It represents the price quoted by the new energy unit m in the kth period of time period t; is the startup cost of conventional unit i in period t;

[0077] CEI i,r is the carbon emission intensity of conventional power generation unit i in province r, which indicates the carbon emission corresponding to unit power generation; represents the benchmark carbon emission intensity of conventional power generation unit i in province r; β c represents the carbon price. It should be noted that due to the long time scale of carbon trading, the present invention assumes that the carbon price is a constant;

[0078] represents the transmission price of the lth inter-provincial tie line; L represents the total number of regional tie lines; and They represent the conventional energy power and the new energy power transmitted by the inter-provincial interconnection line of the first province in time period t respectively; it should be noted that the inter-provincial interconnection line includes a DC interconnection line and an AC interconnection line;

[0079] N dc and N ac They represent the collection of DC interconnection lines and AC interconnection lines between provinces respectively; C L,l represents the network loss penalty factor of tie line l; and Indicates the network loss of AC tie line, DC tie line and DC tie line;

[0080] is the price of excess consumption in province r; P tgc It is the excess consumption amount.

[0081] Specifically, step S02 includes:

[0082] Construct the power generation cost model for each province based on the output of each conventional unit and each new energy unit in each province;

[0083] Based on the output of each conventional unit in each province, a carbon emission cost model for each province is constructed;

[0084] Based on the excess consumption of each province and region, a purchase cost model for excess consumption of each province and region is constructed;

[0085] Based on the power generation cost model of each province and region, the carbon emission cost model of each province and region, and the excess consumption purchase cost model of each province and region, a provincial secondary optimization scheduling cost model is constructed for each province and region.

[0086] Furthermore, the provincial secondary optimization dispatch cost model is expressed as:

[0087]

[0088] Among them, C2, They represent the provincial secondary optimization dispatch cost, provincial power generation cost, provincial carbon emission cost, and provincial excess consumption purchase cost of province r respectively;

[0089] represents the total electricity cost of conventional generators in province r; Represents the total electricity cost of new energy units in province r.

[0090] Specifically, in step S03, the partition power balance constraint includes a regional power balance constraint, a regional positive spare capacity constraint, and a regional negative spare capacity constraint, which are respectively expressed as:

[0091] Regional power balance constraints:

[0092]

[0093] Regional positive reserve capacity constraints:

[0094]

[0095] Regional negative reserve capacity constraints:

[0096]

[0097] in, and They represent the total winning bid output of conventional unit i and new energy unit m in province r during period t; N Tr represents the set of contact lines associated with province r; and They represent the conventional energy and new energy power injected into the tie line l in province r during period t, respectively. Positive numbers represent the power flowing into province r. D j,r,t N represents the load forecast value of province r in period t; Dr represents the total number of loads in province r;

[0098] represents the maximum output of generator set i in province r during time period t; z i,t represents the start and stop status of generator set i in province r during period t; N r represents the total number of generating units in province r, including conventional generating units and new energy generating units; represents the positive reserve capacity demand corresponding to province r; T l,t represents the transmission power of the transmission line l connected to province r in time period t;

[0099] represents the minimum output of generator set i in province r during time period t; It represents the negative spare capacity demand corresponding to province r.

[0100] Specifically, in step S03, the new energy consumption responsibility constraint is expressed as:

[0101]

[0102] in, represents the excess consumption of province r; μ is the new energy consumption responsibility weight of province r; It represents the tradable excess consumption in province r.

[0103] Specifically, in step S03, the inter-regional and inter-provincial interconnection line constraints include DC interconnection line constraints and AC interconnection line constraints.

[0104] Furthermore, the DC tie line constraints include DC tie line transmission power constraints, DC tie line transmission power ramp constraints and DC tie line network loss constraints, which are respectively expressed as:

[0105] DC tie line transmission power constraints:

[0106] DC tie line transmission power ramp constraints:

[0107]

[0108] DC interconnection line loss constraints:

[0109]

[0110] in, and They represent the transmission power, minimum transmission power and maximum transmission power of the DC tie line l in period t respectively; and 0 / 1 variables representing up and down power respectively; Indicates the minimum climbing transmission power of the transmission line; Indicates the minimum climbing transmission power of the transmission line; Represents the linear proportionality coefficient of the network loss of the DC tie line l.

[0111] Furthermore, the AC tie line constraint includes the AC tie line transmission power constraint and the AC tie line network loss constraint, which are respectively expressed as:

[0112] AC tie line transmission power constraints:

[0113]

[0114] AC connection line loss constraints:

[0115]

[0116] in, and They represent the transmission power, minimum transmission power and maximum transmission power of the AC tie line l in time period t; R represents the number of provinces; N r represents the total number of generating units in province r, including conventional generating units and new energy generating units; G i-l represents the power transfer distribution factor of the generator set in province r to the AC tie line; P i,r,t N represents the power generation of generator set i in province r during period t; dc represents the set of inter-provincial DC interconnection lines; G d-a It represents the power transfer distribution factor of the DC tie line to the AC tie line; G represents the transmission power of DC tie line l in period t; j-l N represents the power transfer distribution factor of the load in province r to the AC tie line; Dr represents the total number of loads in province r; D j,r,t represents the load forecast value of province r in period t; Represents the linear proportional coefficient of the network loss of the AC tie line l.

[0117] Specifically, in step S03, the constraints of the thermal power generation unit are expressed as:

[0118]

[0119] Among them, P i,t represents the power generation of thermal power unit i in time period t; P i,min represents the minimum output of thermal power unit i, P i,k,t represents the output of thermal power unit i in the kth segment of the output curve in the tth period; x i,t It is a 0 / 1 variable, indicating the operating status of the thermal power unit; Indicates the maximum power generation of a thermal power unit. Indicates climbing power, T D and T U They respectively represent the maximum and minimum start and stop times of thermal power units.

[0120] Specifically, in step S03, the medium- and long-term supply constraint of new energy is used to decompose the medium- and long-term contract of new energy into each period of the scheduling plan, which is expressed by the formula:

[0121]

[0122] in, represents the daily load curve of the next year predicted for the new energy unit i at the beginning of the year; P MT(t) represents the daily output curve of the power generation units participating in the market bidding; P NMT (t) is the output curve of the generator set not participating in the market; k i The proportion of the contracted electricity of new energy unit i to the total electricity generation participating in the market bidding; Represents the total power generation of new energy units participating in market bidding, The total amount of contracts signed for new energy unit i; In order to decompose the output of each generating unit into the output of each period of the trading day according to the medium- and long-term contracts of new energy, that is, the unit output of the medium- and long-term contracts in each period is not less than the contract decomposition amount of the period; Δt is the interval between adjacent trading periods, which is set to 1 hour in the present invention.

[0123] Specifically, in step S03, when solving the inter-provincial first-level optimization scheduling cost model based on the constraints, the inter-provincial first-level optimization scheduling cost model is solved based on the load curve and the boundary values ​​in the constraints, and the output of each unit in each time period, the operating status of each unit, the network loss of each interconnection line, the conventional energy power transmitted by the interconnection lines (including DC interconnection lines and AC interconnection lines) between provinces, the new energy power transmitted by the interconnection lines (including DC interconnection lines and AC interconnection lines) between provinces, etc. are obtained.

[0124] Exemplarily, a solver such as Cplex is used for solving.

[0125] Furthermore, according to the solution result, an inter-provincial optimal dispatching scheme is determined, and the inter-provincial optimal dispatching scheme includes the conventional energy power transmitted by each of the interconnection lines and the new energy power transmitted by each of the interconnection lines.

[0126] Furthermore, the inter-provincial optimization scheduling plan, i.e., the conventional energy power transmitted by the interconnection lines between provinces and the new energy power transmitted by the interconnection lines between provinces, is substituted into step 04 as a boundary condition.

[0127] Specifically, in step S04, the line power flow constraint is expressed as:

[0128]

[0129] The cross-sectional flow constraint is expressed as:

[0130]

[0131] Among them, G i-b represents the power transfer distribution factor of the generator set i to the line in province r, G l-b represents the power transfer distribution factor of the tie line l to the line, G j-b represents the power transfer distribution factor of the generator set i to the line in province r; represents the maximum transmission power of the bth transmission line in province r; T l,t represents the transmission power of the transmission line l connected to province r;

[0132] represents the maximum transmission power of section s within province r; G i-s G represents the power transfer distribution factor of the section flow of the generator set i in the province r; l-s G represents the power transfer distribution factor of the tie line l to the cross-section flow; j-s It represents the power transfer distribution factor of generator i to the section flow in province r.

[0133] Furthermore, the conventional energy power transmitted by each tie line and the new energy power transmitted by each tie line obtained in step S03 are the line flow constraints and T l,t .

[0134] Furthermore, in step S04, the provincial secondary optimization scheduling cost model is solved based on the load curve and the boundary values ​​in each constraint condition, and a solver such as Cplex is used to solve the model to obtain the optimal scheduling plan for each province, including the output of each conventional unit, the output of each new energy unit and the operating status of each generator unit in each time period in each province.

[0135] The present embodiment discloses a method for optimizing green electricity dispatch across provinces and regions taking into account the constraints of AC and DC interconnection lines. By considering the constraints of AC and DC interconnection lines for inter-provincial dispatch and constructing a first-level optimization dispatch cost model between provinces and a second-level optimization dispatch cost model within a province, the transmission power of inter-provincial and inter-regional interconnection lines and the dispatch plan for each unit within each province are obtained step by step, thereby effectively reducing the power generation cost of the power system and improving the consumption of new energy.

[0136] By constructing DC interconnection line constraints and AC interconnection line constraints, the transmission power limitation and network loss are taken into consideration to accurately model inter-provincial scheduling; by constructing line flow constraints and section flow constraints, the transmission of intra-provincial lines is accurately modeled to improve the accuracy and scientificity of solving scheduling solutions.

[0137] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for optimizing green power dispatch across provinces and regions taking into account AC and DC interconnection line constraints, characterized in that: The steps include: Based on the output of each conventional unit, the output of each new energy unit, the conventional energy power transmitted by each inter-provincial interconnection line, and the new energy power transmitted by each inter-provincial interconnection line within the scope of inter-provincial dispatch, a provincial first-level optimization dispatch cost model is constructed; Based on the output of each conventional unit and each new energy unit in each province, a provincial secondary optimization dispatch cost model is constructed; With the goal of minimizing the inter-provincial first-level optimization dispatching cost, the inter-provincial first-level optimization dispatching cost model is solved based on the regional power balance constraints, new energy consumption responsibility constraints, cross-regional and cross-provincial interconnection line constraints, thermal power unit constraints, and new energy medium- and long-term supply constraints to obtain the conventional energy power transmitted by each interconnection line and the new energy power transmitted by each interconnection line; With the goal of minimizing the cost of the provincial secondary optimization dispatching, the provincial secondary optimization dispatching cost model of each province is solved based on the conventional energy power transmitted by each of the interconnection lines, the new energy power transmitted by each of the interconnection lines, and the line flow constraints and section flow constraints, and the output of each conventional unit and each new energy unit in each province is obtained.

2. The optimization scheduling method according to claim 1, characterized in that: The inter-provincial first-level optimization dispatch cost model is constructed based on the output of each conventional unit, the output of each new energy unit, the conventional energy power transmitted by each inter-provincial interconnection line, and the new energy power transmitted by each inter-provincial interconnection line within the scope of inter-provincial dispatch, including: Constructing a power generation cost model based on the output of each conventional unit and the output of each new energy unit; Constructing a carbon emission cost model based on the output of each conventional unit; Constructing a tie line transmission cost model based on the conventional energy power transmitted by each tie line and the new energy power transmitted by each tie line; Constructing a network loss cost model based on the network loss of each of the tie lines; Construct an excess consumption purchase cost model based on the excess consumption of each province and region; A first-level inter-provincial optimization dispatching cost model is constructed based on the power generation cost model, carbon emission cost model, interconnection line transmission cost model, network loss cost model and excess consumption purchase cost model.

3. The optimization scheduling method according to claim 2, characterized in that: Based on the output of each conventional unit and each new energy unit in each province, the provincial secondary optimization dispatch cost model for each province is constructed, including: Construct the power generation cost model for each province based on the output of each conventional unit and each new energy unit in each province; Based on the output of each conventional unit in each province, a carbon emission cost model for each province is constructed; Based on the excess consumption of each province and region, a purchase cost model for excess consumption of each province and region is constructed; Based on the power generation cost model of each province and region, the carbon emission cost model of each province and region, and the excess consumption purchase cost model of each province and region, a provincial secondary optimization scheduling cost model is constructed for each province and region.

4. The optimization scheduling method according to any one of claims 1 to 3, characterized in that: The inter-regional and inter-provincial tie line constraints include DC tie line constraints and AC tie line constraints; the DC tie line constraints include DC tie line transmission power constraints, DC tie line transmission power ramp constraints and DC tie line network loss constraints, which are respectively expressed as: in, and They represent the transmission power, minimum transmission power and maximum transmission power of the DC tie line l in period t respectively; and 0 / 1 variables representing up and down power respectively; Indicates the minimum climbing transmission power of the transmission line; Indicates the minimum climbing transmission power of the transmission line; Represents the linear proportionality coefficient of the network loss of the DC tie line l.

5. The optimization scheduling method according to claim 4, characterized in that: The AC tie line constraint includes AC tie line transmission power constraint and AC tie line network loss constraint, which are respectively expressed as: in, and They represent the transmission power, minimum transmission power and maximum transmission power of the AC tie line l in time period t; R represents the number of provinces; n r represents the total number of generating units in province r, including conventional generating units and new energy generating units; G i-l represents the power transfer distribution factor of the generator set in province r to the AC tie line; P i,r,t N represents the power generation of generator set i in province r during period t; dc represents the set of inter-provincial DC interconnection lines; G d-a It represents the power transfer distribution factor of the DC tie line to the AC tie line; G represents the transmission power of DC tie line l in period t; j-l N represents the power transfer distribution factor of the load in province r to the AC tie line; Dr represents the total number of loads in province r; D j,r,t represents the load forecast value of province r in period t; K i AC Represents the linear proportional coefficient of the network loss of the AC tie line l.

6. The optimization scheduling method according to claim 5, characterized in that: The inter-provincial first-level optimization scheduling cost model is expressed as: Among them, C1, C gen , C car , C tra , C was , C tgc They represent the inter-provincial first-level optimization dispatching cost, power generation cost, carbon emission cost, interconnection line transmission cost, network loss cost and excess consumption purchase cost respectively; represents the total electricity cost of conventional generator sets; represents the total electricity cost of the new energy unit; T represents the total number of time periods; N Er and N GEr They represent the number of conventional generating units and the number of new energy generating units that provide electricity to province r; K represents the total number of segments of the quotation; represents the power output of conventional unit i in the kth segment of time period t; α i,k,r,t represents the declared price of the electric energy of the conventional unit i in the kth period of time period t; represents the output of the new energy unit m in the kth segment of time period t; γ m,k,r,t It represents the price quoted by the new energy unit m in the kth period of time period t; is the startup cost of conventional unit i in period t; is the carbon emission intensity of conventional generator set i; represents the benchmark carbon emission intensity corresponding to conventional power generation unit i; β c represents the carbon price; represents the transmission price of the lth inter-provincial tie line; L represents the total number of regional tie lines; and They represent the conventional energy and new energy power transmitted by the lth inter-provincial interconnection line in time period t respectively; N dc and N ac represent the collection of inter-provincial DC interconnection lines and AC interconnection lines respectively; C L,l represents the network loss penalty factor of tie line l; and Indicates the network loss of AC tie line, DC tie line and DC tie line; C tgcc is the national excess consumption price; P tgc It is the excess consumption amount.

7. The optimization scheduling method according to claim 6, characterized in that: The provincial secondary optimization scheduling cost model is expressed as: Among them, C2, They represent the provincial secondary optimization dispatch cost, provincial power generation cost, provincial carbon emission cost, and provincial excess consumption purchase cost of province r respectively; represents the total electricity cost of conventional generators in province r; Represents the total electricity cost of new energy units in province r.

8. The optimization scheduling method according to claim 7, characterized in that: The partition power balance constraint includes a regional power balance constraint, a regional positive spare capacity constraint and a regional negative spare capacity constraint, which are respectively expressed as: in, and They represent the total winning bid output of conventional unit i and new energy unit m in province r during period t; N Tr represents the set of contact lines associated with province r; and They represent the conventional energy and new energy power injected into the tie line l in province r during period t, respectively. Positive numbers represent the power flowing into province r. D j,r,t represents the load forecast value of province r in period t; represents the maximum output of generator set i in province r during time period t; z i,t represents the start and stop status of generator set i in province r during period t; represents the positive reserve capacity demand corresponding to province r; T l,t represents the transmission power of the transmission line l connected to province r in time period t; represents the minimum output of generator set i in province r during time period t; It represents the negative spare capacity demand corresponding to province r.

9. The optimization scheduling method according to claim 8, characterized in that: The new energy consumption responsibility constraint is expressed as: in, represents the excess consumption of province r; μ is the new energy consumption responsibility weight of province r; It represents the tradable excess consumption in province r.

10. The optimization scheduling method according to claim 9, characterized in that: The line flow constraint and section flow constraint are respectively expressed as: Among them, G i-b represents the power transfer distribution factor of the generator set i to the line in province r, G l-b represents the power transfer distribution factor of the tie line l to the line, G j-b represents the power transfer distribution factor of the line from generator set i in province r; represents the maximum transmission power of the bth transmission line in province r; T l,t represents the transmission power of the transmission line l connected to province r; represents the maximum transmission power of section s within province r; G i-5 G represents the power transfer distribution factor of the section flow of the generator set i in the province r; l-s G represents the power transfer distribution factor of the tie line l to the cross-section flow; j-s It represents the power transfer distribution factor of generator i to the section flow in province r.

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