A multi-type load power grid low-carbon optimization scheduling method and system

Abstract

The application discloses a multi-type load power grid low-carbon optimal scheduling method and system, which comprises the following steps: firstly, a load scheduling model is constructed with the target of maximum new energy consumption in a region; then, the load scheduling model is solved to obtain the regional load scheduling power in each period in a scheduling period; then, based on the regional load scheduling power required in each period in the scheduling period, the scheduling cost and carbon emission of the regional residential load, commercial load, industrial load and electric vehicle adjustable load are comprehensively considered to establish a multi-type load power grid low-carbon scheduling model; finally, the multi-type load power grid low-carbon scheduling model is solved to obtain a multi-type load power grid low-carbon scheduling scheme. The application comprehensively considers the scheduling characteristics of the multi-type load such as the residential load, commercial load, industrial load and electric vehicle adjustable load and the time-space variation of the power grid node carbon emission factor, and takes the new energy consumption as the target, so that the power grid scheduling cost and the regional power grid carbon emission are reduced.

Description

Technical Field

[0001] This invention belongs to the field of power technology, specifically relating to a low-carbon optimization scheduling method and system for multi-type load power grids. Background Technology

[0002] With the rapid development of new energy vehicle technology and the increasing awareness of green travel, the market penetration rate of new energy vehicles is getting higher and higher. The sharp increase in the charging demand of new energy vehicles has had a significant impact on the load of the power grid. Based on the differences in electric vehicle charging demand and the demand response characteristics of different types of loads during power grid dispatching, optimizing the power grid load side dispatching with the goal of minimizing dispatching costs and carbon emissions not only helps to increase the absorption rate of new energy and enhance power grid stability, but also effectively reduces the carbon emissions of the power grid.

[0003] Traditional power grid dispatching methods often formulate corresponding dispatching strategies for different types of loads, focusing more on the safety and economy of the power grid while neglecting environmental protection. Low-carbon dispatching strategies for power grids that include multiple types of loads such as electric vehicles have not taken into account the impact of the differentiated charging needs of electric vehicles on regional power grid dispatching, and have not matched dispatching strategies for different time periods with real-time changes in electricity carbon emission factors, which is not conducive to the flexible dispatching of flexible loads and the low-carbon operation of the power grid. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems in the existing technology by providing a low-carbon optimized scheduling method and system for multi-type load power grids.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] Firstly, this invention proposes a low-carbon optimized scheduling method for multi-type load power grids, comprising:

[0007] S1. Construct a load dispatching model with the goal of maximizing the absorption of new energy sources in the region;

[0008] S2. Solve the load scheduling model to obtain the regional load scheduling power for each time period within the scheduling cycle;

[0009] S3. Based on the required load dispatch power of each time period in the dispatch cycle, and taking into account the dispatch cost and carbon emissions of regional residential load, commercial load, industrial load, and electric vehicle adjustable load, a low-carbon dispatch model for the power grid with multiple types of loads is established.

[0010] S4. Solve the low-carbon dispatch model of the power grid with multiple types of loads to obtain the low-carbon dispatch scheme of the power grid with multiple types of loads.

[0011] The objective function of the low-carbon dispatch model for multi-type load power grids includes:

[0012]

[0013] R dis,t =R ind,t +R com,t +R EV,t

[0014]

[0015]

[0016] In the above formula, F t The indicator for low-carbon dispatching of power grid load is κ, where κ is the weighting coefficient and R is the weighting coefficient. dis,t Let t be the power grid load dispatching cost for time period t. These represent the regional load power and load dispatch power during time period t, respectively, and γ car,t Let E be the carbon price cost during period t. af,t E be,t These represent the total carbon emissions of the regional power grid before and after the dispatch, R. ind,t R com,t R EV,t The dispatch costs for industrial load, commercial load, and electric vehicle load, respectively, are γ. ind The compensation unit price for industrial load, λ ind,t , λ com,t , λ EV,t The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. These are the compensation unit price and power reduction for commercial load of level k, respectively, where K is the level of commercial load;

[0017] The constraints of the low-carbon dispatch model for multi-type load power grids include power balance constraints, electric vehicle charging constraints, distribution network power flow constraints, and load reduction constraints.

[0018] The Calculated based on the following formula:

[0019]

[0020] In the above formula, x j,t , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let M be the minimum charging power of the j-th electric vehicle, M be the number of electric vehicles connected to the grid, and SOC be the minimum charging power. j (t) represents the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. η j , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively, and Δt be the charging time of the j-th electric vehicle during time period t.

[0021] The E af,t E be,t Calculated based on the following formula:

[0022]

[0023] In the above formula, E t C represents the total carbon emissions of the regional power grid during time period t. i,t Let be the carbon emission factor of load node i during time period t. Let be the load power of load node i during time period t, and N be the set of nodes in the regional power grid. Let ρ be the power injected into load node i at time t, and ρ be the power injected into the generator unit connected to load node i. i,t , Here, denoted as the carbon flux density of load node i during time period t, and the carbon potential of the generator unit connected to load node i, respectively.

[0024] The power balance constraints include:

[0025]

[0026] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0027] The electric vehicle charging constraints include:

[0028]

[0029] In the above formula, SOC j (t) represents the state of charge of the j-th electric vehicle during time period t. Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively.

[0030] The power flow constraints of the distribution network include:

[0031] P l,min ≤P l ≤P l,max

[0032] In the above formula, P l For the active power flow of the line, P l,min P l,maxThese are the lower and upper limits of the line transmission power, respectively.

[0033] The load reduction constraint includes:

[0034] t min ≤Δt′≤t max

[0035]

[0036] In the above formula, Δt′ is the translation time of the industrial load, and t min t max These represent the minimum and maximum shift times for the industrial load, respectively. These represent the lower and upper limits of commercial load, respectively.

[0037] The objective function of the load scheduling model includes:

[0038]

[0039] In the above formula, Q net For the net load of the regional power grid, These represent the regional load power and load dispatch power during time period t, respectively. PV (t), P WP (t) represents the power output of photovoltaic and wind turbines in the region during time period t, and T is the dispatch period;

[0040] The constraints of the load dispatching model include:

[0041] Power balance constraints

[0042]

[0043] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0044] Regional load dispatch power constraints

[0045]

[0046] In the above formula, This represents the maximum load dispatch power of the regional power grid.

[0047] Secondly, this invention proposes a low-carbon optimization scheduling system for multi-type load power grids, including a load scheduling model construction module, a load scheduling model solving module, a low-carbon scheduling model construction module for multi-type load power grids, and a low-carbon scheduling model solving module for multi-type load power grids.

[0048] The multi-type load power grid low-carbon dispatch model is used to construct a load dispatch model with the goal of maximizing the absorption of new energy sources in the region.

[0049] The load scheduling model solving module is used to solve the load scheduling model and obtain the regional load scheduling power for each time period within the scheduling cycle.

[0050] The multi-type load power grid low-carbon dispatch model construction module is used to establish a multi-type load power grid low-carbon dispatch model based on the required load dispatch power of each time period in the dispatch cycle, and comprehensively consider the dispatch cost and carbon emissions of regional residential load, commercial load, industrial load and electric vehicle adjustable load.

[0051] The multi-type load power grid low-carbon dispatching model solving module is used to solve the multi-type load power grid low-carbon dispatching model and obtain the multi-type load power grid low-carbon dispatching scheme.

[0052] The objective function of the low-carbon dispatch model for multi-type load power grids includes:

[0053]

[0054] R dis,t =R ind,t +R com,t +R EV,t

[0055]

[0056] In the above formula, F t The indicator for low-carbon dispatching of power grid load is κ, where κ is the weighting coefficient and R is the weighting coefficient. dis,t Let t be the power grid load dispatching cost for time period t. These represent the regional load power and load dispatch power during time period t, respectively, and γ car,t Let E be the carbon price cost during period t. af,t E be,t These represent the total carbon emissions of the regional power grid before and after the dispatch, R. ind,t R com,t R EV,t The dispatch costs for industrial load, commercial load, and electric vehicle load, respectively, are γ. ind The compensation unit price for industrial load, λ ind,t , λ com,t , λ EV,t The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. These are the compensation unit price and power reduction for commercial load of level k, respectively, where K is the level of commercial load;

[0057] The constraints of the low-carbon dispatch model for multi-type load power grids include power balance constraints, electric vehicle charging constraints, distribution network power flow constraints, and load reduction constraints.

[0058] The Calculated based on the following formula:

[0059]

[0060]

[0061] In the above formula, x j,t , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let M be the minimum charging power of the j-th electric vehicle, M be the number of electric vehicles connected to the grid, and SOC be the minimum charging power. j (t) represents the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. η j , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively, and Δt be the charging time of the j-th electric vehicle during time period t.

[0062] The E af,t E be,t Calculated based on the following formula:

[0063]

[0064] In the above formula, E t C represents the total carbon emissions of the regional power grid during time period t. i,t Let be the carbon emission factor of load node i during time period t. Let be the load power of load node i during time period t, and N be the set of nodes in the regional power grid. Let ρ be the power injected into load node i at time t, and ρ be the power injected into the generator unit connected to load node i. i,t , Here, denoted as the carbon flux density of load node i during time period t, and the carbon potential of the generator unit connected to load node i, respectively.

[0065] The power balance constraints include:

[0066]

[0067] In the above formula, P loss (t), P grid (t), P MT(t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0068] The electric vehicle charging constraints include:

[0069]

[0070] In the above formula, SOC j (t) represents the state of charge of the j-th electric vehicle during time period t. Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively.

[0071] The power flow constraints of the distribution network include:

[0072] P l,min ≤P l ≤P l,max

[0073] In the above formula, P l For the active power flow of the line, P l,min P l,max These are the lower and upper limits of the line transmission power, respectively.

[0074] The load reduction constraint includes:

[0075] t min ≤Δt′≤t max

[0076]

[0077] In the above formula, Δt′ is the translation time of the industrial load, and t min t max These represent the minimum and maximum shift times for the industrial load, respectively. These represent the lower and upper limits of commercial load, respectively.

[0078] The objective function of the load scheduling model includes:

[0079]

[0080] In the above formula, Q net For the net load of the regional power grid, These represent the regional load power and load dispatch power during time period t, respectively. PV (t), P WP (t) represents the power output of photovoltaic and wind turbines in the region during time period t, and T is the dispatch period;

[0081] The constraints of the load dispatching model include:

[0082] Power balance constraints

[0083]

[0084] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0085] Regional load dispatch power constraints

[0086]

[0087] In the above formula, This represents the maximum load dispatch power of the regional power grid.

[0088] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0089] 1. This invention discloses a low-carbon optimization scheduling method for multi-type load power grids. First, a load scheduling model is constructed with the goal of maximizing the absorption of new energy sources in the region. Then, the load scheduling model is solved to obtain the regional load scheduling power for each time period within the scheduling cycle. Based on the required regional load scheduling power for each time period within the scheduling cycle, and considering the scheduling costs and carbon emissions of regional residential loads, commercial loads, industrial loads, and adjustable loads from electric vehicles, a low-carbon scheduling model for multi-type load power grids is established. Finally, the low-carbon scheduling model for multi-type load power grids is solved to obtain a low-carbon scheduling scheme for multi-type load power grids. This method comprehensively considers the scheduling characteristics of multiple types of loads, including residential loads, commercial loads, industrial loads, and adjustable loads from electric vehicles, with the goal of improving the absorption of new energy sources, reducing power grid scheduling costs while reducing regional power grid carbon emissions.

[0090] 2. The present invention provides a low-carbon optimization scheduling method for multi-type load power grids, which takes into account the impact of the differentiated charging demand of electric vehicles on regional power grid scheduling. At the same time, it matches the scheduling strategies for different time periods with the real-time changing power carbon emission factors, which is conducive to the flexible scheduling of flexible loads and the low-carbon operation of the power grid. Attached Figure Description

[0091] Figure 1 This is a flowchart of the method described in this invention.

[0092] Figure 2 This is a structural diagram of the system described in this invention. Detailed Implementation

[0093] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0094] Example 1:

[0095] A low-carbon optimization scheduling method for multi-type load power grids, such as Figure 1 As shown, follow these steps:

[0096] 1. Construct a load dispatching model with the goal of maximizing the absorption of new energy sources in the region.

[0097] Based on the regional photovoltaic and wind power generation output, the net load of the power grid is minimized when the load curve consumes as much renewable energy as possible. Therefore, the following regional power grid load dispatching model is established with the objective function of minimizing the regional power grid net load:

[0098]

[0099] In the above formula, Q net For the net load of the regional power grid, These represent the regional load power and load dispatch power during time period t, respectively. PV (t), P WP (t) represents the power output of photovoltaic and wind turbines in the region during time period t, and T is the dispatch period;

[0100] The constraints of the load dispatching model include:

[0101] Power balance constraints

[0102]

[0103] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0104] Regional load dispatch power constraints

[0105]

[0106] In the above formula, This represents the maximum load dispatch power of the regional power grid.

[0107] 2. Solve the above load dispatching model to obtain the regional load dispatching power for each time period within the dispatching cycle.

[0108] 3. Classify the load types of regional power grid nodes and calculate the dynamic carbon emission factor C of each load node based on power flow information. i,t Based on meter information, the node load is divided into industrial load, commercial load, residential load, and electric vehicle charging load, among which C i,t The following formula was used to calculate:

[0109]

[0110] In the above formula, Let ρ be the power injected into load node i at time t, and ρ be the power injected into the generator unit connected to load node i. i,t , Here, denoted as the carbon flux density of load node i during time period t, and the carbon potential of the generator unit connected to load node i, respectively.

[0111] 4. Calculate the dispatch power of electric vehicle load based on electric vehicle charging demand:

[0112]

[0113] In the above formula, Let x be the dispatch power of the electric vehicle load in the region during time period t. j,t , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let M be the minimum charging power of the j-th electric vehicle, M be the number of electric vehicles connected to the grid, and SOC be the minimum charging power. j (t) represents the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. η j , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively, and Δt be the charging time of the j-th electric vehicle during time period t.

[0114] 5. Based on the required load dispatch power of each time period within the dispatch cycle, and taking into account the dispatch costs and carbon emissions of regional residential load, commercial load, industrial load, and adjustable load of electric vehicles, set low-carbon dispatch indicators for power grid load and establish a low-carbon dispatch model for power grid with multiple types of loads.

[0115] The objective function of this model is:

[0116]

[0117] R dis,t =R ind,t +R com,t +R EV,t

[0118]

[0119] In the above formula, F t R is a low-carbon dispatch index for power grid load, where κ is a weighting coefficient with a value range of (0, 1). dis,t Let t be the power grid load dispatching cost for time period t. These represent the regional load power and load dispatch power during time period t, respectively, and γ car,t Let E be the carbon price cost during period t.af,t E be,t These represent the total carbon emissions of the regional power grid before and after the dispatch, R. ind,t R com,t R EV,t The dispatch costs for industrial load, commercial load, and electric vehicle load, respectively, are γ. ind The compensation unit price for industrial load, λ ind,t , λ com,t , λ EV,t The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. These represent the compensation unit price and power reduction for commercial load of level k, where K is the level of the commercial load, and E... t C represents the total carbon emissions of the regional power grid during time period t. i,t Let be the carbon emission factor of load node i during time period t. Let be the load power of load node i during time period t, and N be the set of nodes in the regional power grid;

[0120] The constraints include:

[0121] Power balance constraints

[0122]

[0123] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0124] Electric vehicle charging constraints

[0125]

[0126] In the above formula, SOC j (t) represents the state of charge of the j-th electric vehicle during time period t. Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively.

[0127] Distribution network power flow constraints

[0128] P l,min ≤P l ≤P l,max

[0129] In the above formula, P l For the active power flow of the line, P l,min P l,max These are the lower and upper limits of the line transmission power, respectively.

[0130] Load reduction constraints

[0131] t min ≤Δt′≤t max

[0132]

[0133] In the above formula, Δt′ is the translation time of the industrial load, and t min t max These represent the minimum and maximum shift times for the industrial load, respectively. These represent the lower and upper limits of commercial load, respectively.

[0134] 6. Solve the above low-carbon dispatch model for multi-type load power grids to obtain low-carbon dispatch schemes for multi-type load power grids, including the dispatch power of industrial loads, commercial loads, and electric vehicle loads on the load side.

[0135] Example 2:

[0136] A low-carbon optimization scheduling system for multi-type load power grids includes a load scheduling model construction module, a load scheduling model solving module, a low-carbon scheduling model construction module for multi-type load power grids, and a low-carbon scheduling model solving module for multi-type load power grids.

[0137] The multi-type load power grid low-carbon dispatch model is used to construct a load dispatch model with the goal of maximizing the absorption of new energy sources in a region. The objective function of this model is:

[0138]

[0139] In the above formula, Q net For the net load of the regional power grid, These represent the regional load power and load dispatch power during time period t, respectively. PV (t), P WP (t) represents the power output of photovoltaic and wind turbines in the region during time period t, and T is the dispatch period;

[0140] The constraints of the load dispatching model include:

[0141] Power balance constraints

[0142]

[0143] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0144] Regional load dispatch power constraints

[0145]

[0146] In the above formula, This represents the maximum load dispatch power of the regional power grid.

[0147] The load scheduling model solving module is used to solve the load scheduling model and obtain the regional load scheduling power for each time period within the scheduling cycle.

[0148] The multi-type load power grid low-carbon dispatch model construction module is used to establish a multi-type load power grid low-carbon dispatch model based on the required load dispatch power of the region in each time period within the dispatch cycle, comprehensively considering the dispatch costs and carbon emissions of regional residential load, commercial load, industrial load, and adjustable load of electric vehicles. The objective function of this model is:

[0149]

[0150] R dis,t =R ind,t +R com,t +R EV,t

[0151]

[0152]

[0153] In the above formula, F t The indicator for low-carbon dispatching of power grid load is κ, where κ is the weighting coefficient and R is the weighting coefficient. dis,t Let t be the power grid load dispatching cost for time period t. These represent the regional load power and load dispatch power during time period t, respectively, and γ car,t Let E be the carbon price cost during period t. af,t E be,t These represent the total carbon emissions of the regional power grid before and after the dispatch, R. ind,t R com,t R EV,t The dispatch costs for industrial load, commercial load, and electric vehicle load, respectively, are γ. ind The compensation unit price for industrial load, λ ind,t , λ com,t , λ EV,t The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. These represent the compensation unit price and power reduction for commercial load of level k, where K is the level of the commercial load, and E... t C represents the total carbon emissions of the regional power grid during time period t. i,tLet be the carbon emission factor of load node i during time period t. Let be the load power of load node i during time period t, and N be the set of nodes in the regional power grid. Let ρ be the power injected into load node i at time t, and ρ be the power injected into the generator unit connected to load node i. i,t , Let x be the carbon flux density at load node i during time period t, x be the carbon potential of the generator unit connected to load node i, and x be the carbon flux density at load node i during time period t. j,t , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let M be the minimum charging power of the j-th electric vehicle, M be the number of electric vehicles connected to the grid, and SOC be the minimum charging power. j (t) represents the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. η j , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively, and Δt be the charging time of the j-th electric vehicle during time period t.

[0154] The constraints include:

[0155] Power balance constraints

[0156]

[0157] In the above formula, P loss (t), P grid (t), P MT (t) represents the power loss, power purchased from the main grid, and gas turbine power during time period t, respectively;

[0158] Electric vehicle charging constraints

[0159]

[0160] In the above formula, SOC j (t) represents the state of charge of the j-th electric vehicle during time period t. Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively.

[0161] Distribution network power flow constraints

[0162] P l,min ≤P l ≤P l,max

[0163] In the above formula, P l For the active power flow of the line, P l,min P l,maxThese are the lower and upper limits of the line transmission power, respectively.

[0164] Load reduction constraints

[0165] t min ≤Δt′≤t max

[0166]

[0167] In the above formula, Δt′ is the translation time of the industrial load, and t min t max These represent the minimum and maximum shift times for the industrial load, respectively. These represent the lower and upper limits of commercial load, respectively.

[0168] The multi-type load power grid low-carbon dispatch model solving module is used to solve the multi-type load power grid low-carbon dispatch model and obtain the multi-type load power grid low-carbon dispatch scheme, including the dispatch power of industrial load, commercial load and electric vehicle load on the load side.

Claims

1. A low-carbon optimized dispatching method for multi-type load power grids, characterized in that, The method includes: S1. Construct a load dispatching model with the goal of maximizing the absorption of new energy sources in the region; S2. Solve the load scheduling model to obtain the regional load scheduling power for each time period within the scheduling cycle; S3. Based on the required load dispatch power of each time period in the dispatch cycle, and taking into account the dispatch cost and carbon emissions of regional residential load, commercial load, industrial load, and electric vehicle adjustable load, a low-carbon dispatch model for the power grid with multiple types of loads is established. The objective function of the low-carbon dispatch model for multi-type load power grids includes: ； ； ； ； ； ； In the above formula, As an indicator for low-carbon dispatching of power grid load, These are the weighting coefficients. Let t be the power grid load dispatching cost for time period t. , These represent the regional load power and load dispatch power during time period t, respectively. Let t be the carbon price cost during period t. , These represent the total carbon emissions of the regional power grid before and after the dispatch, respectively. , , The dispatch costs are respectively for industrial load, commercial load, and electric vehicle load. The compensation unit price for industrial load, , , The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. , , These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. , These represent the compensation unit price and power reduction for commercial load of level k, respectively. The level of commercial load; The constraints of the low-carbon dispatch model for multi-type load power grids include power balance constraints, electric vehicle charging constraints, distribution network power flow constraints, and load reduction constraints. S4. Solve the low-carbon dispatch model of the power grid with multiple types of loads to obtain the low-carbon dispatch scheme of the power grid with multiple types of loads.

2. The low-carbon optimized dispatching method for multi-type load power grids according to claim 1, characterized in that, The Calculated based on the following formula: ； ； ； In the above formula, , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let be the minimum charging power of the j-th electric vehicle. The number of electric vehicles connected to the power grid. Let j be the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. , , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively. The charging time of the j-th electric vehicle during time period t; The , Calculated based on the following formula: ； ； In the above formula, The total carbon emissions of the regional power grid during time period t. Let be the carbon emission factor of load node i during time period t. Let i be the load power of load node i during time period t. It is a set of nodes within a regional power grid. , Let be the power injected into load node i at time t, and be the injected power of the generator unit connected to load node i, respectively. , Here, denoted as the carbon flux density of load node i during time period t, and the carbon potential of the generator unit connected to load node i, respectively.

3. A low-carbon optimized dispatching method for multi-type load power grids according to claim 1 or 2, characterized in that, The power balance constraints include: ； In the above formula, , , These represent the power loss during time period t, the power purchased from the main grid, and the gas turbine power, respectively. The electric vehicle charging constraints include: ； In the above formula, Let j be the state of charge of the j-th electric vehicle during time period t. , Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively. The power flow constraints of the distribution network include: ； In the above formula, For the power flow of the line, , These are the lower and upper limits of the line transmission power, respectively. The load reduction constraint includes: ； In the above formula, The shift time of the industrial load. , These represent the minimum and maximum shift times for the industrial load, respectively. , These represent the lower and upper limits of commercial load, respectively.

4. The low-carbon optimized dispatching method for multi-type load power grids according to claim 1, characterized in that, The objective function of the load scheduling model includes: ； In the above formula, For the net load of the regional power grid, , These represent the regional load power and load dispatch power during time period t, respectively. , These represent the power output of photovoltaic and wind turbines in the region during time period t. The scheduling period; The constraints of the load dispatching model include: Power balance constraints ； In the above formula, , , These represent the power loss during time period t, the power purchased from the main grid, and the gas turbine power, respectively. Regional load dispatch power constraints ； In the above formula, This represents the maximum load dispatch power of the regional power grid.

5. A low-carbon optimized dispatching system for multi-type load power grids, characterized in that, The system includes a load scheduling model construction module, a load scheduling model solving module, a multi-type load power grid low-carbon scheduling model construction module, and a multi-type load power grid low-carbon scheduling model solving module. The multi-type load power grid low-carbon dispatch model is used to construct a load dispatch model with the goal of maximizing the absorption of new energy sources in the region. The load scheduling model solving module is used to solve the load scheduling model and obtain the regional load scheduling power for each time period within the scheduling cycle. The multi-type load power grid low-carbon dispatch model construction module is used to establish a multi-type load power grid low-carbon dispatch model based on the required load dispatch power of each time period in the dispatch cycle, and comprehensively consider the dispatch cost and carbon emissions of regional residential load, commercial load, industrial load and electric vehicle adjustable load. The objective function of the low-carbon dispatch model for multi-type load power grids includes: ； ； ； ； ； ； In the above formula, As an indicator for low-carbon dispatching of power grid load, These are the weighting coefficients. Let t be the power grid load dispatching cost for time period t. , These represent the regional load power and load dispatch power during time period t, respectively. Let t be the carbon price cost during period t. , These represent the total carbon emissions of the regional power grid before and after the dispatch, respectively. , , The dispatch costs are respectively for industrial load, commercial load, and electric vehicle load. The compensation unit price for industrial load, , , The electricity prices for industrial load, commercial load, and electric vehicle load during time period t are respectively. , , These represent the dispatch power for regional industrial load, commercial load, and electric vehicle load during time period t, respectively. , These represent the compensation unit price and power reduction for commercial load of level k, respectively. The level of commercial load; The constraints of the low-carbon dispatch model for multi-type load power grids include power balance constraints, electric vehicle charging constraints, distribution network power flow constraints, and load reduction constraints. The multi-type load power grid low-carbon dispatch model solving module is used to solve the multi-type load power grid low-carbon dispatch model and obtain multi-type load power grid low-carbon dispatch schemes, including industrial loads, commercial loads and electric vehicle loads on the load side.

6. A low-carbon optimized dispatching system for multi-type load power grids according to claim 5, characterized in that, The Calculated based on the following formula: ； ； ； In the above formula, , Let be the scheduling status and charging power of the j-th electric vehicle during time period t, respectively. Let be the minimum charging power of the j-th electric vehicle. The number of electric vehicles connected to the power grid. Let j be the state of charge of the j-th electric vehicle during time period t. Let J be the minimum charge requirement for the j-th electric vehicle. , , Let be the initial state of charge, charging efficiency, and rated battery capacity of the j-th electric vehicle, respectively. The charging time of the j-th electric vehicle during time period t; The , Calculated based on the following formula: ； ； In the above formula, The total carbon emissions of the regional power grid during time period t. Let be the carbon emission factor of load node i during time period t. Let i be the load power of load node i during time period t. It is a set of nodes within a regional power grid. , Let be the power injected into load node i at time t, and be the injected power of the generator unit connected to load node i, respectively. , Here, denoted as the carbon flux density of load node i during time period t, and the carbon potential of the generator unit connected to load node i, respectively.

7. A low-carbon optimized dispatching system for multi-type load power grids according to claim 5 or 6, characterized in that, The power balance constraints include: ； In the above formula, , , These represent the power loss during time period t, the power purchased from the main grid, and the gas turbine power, respectively. The electric vehicle charging constraints include: ； In the above formula, Let j be the state of charge of the j-th electric vehicle during time period t. , Let be the minimum and maximum charge requirements of the j-th electric vehicle, respectively. The power flow constraints of the distribution network include: ； In the above formula, For the power flow of the line, , These are the lower and upper limits of the line transmission power, respectively. The load reduction constraint includes: ； In the above formula, The shift time of the industrial load. , These represent the minimum and maximum shift times for the industrial load, respectively. , These represent the lower and upper limits of commercial load, respectively.

8. A low-carbon optimized dispatching system for multi-type load power grids according to claim 5, characterized in that, The objective function of the load scheduling model includes: ； In the above formula, For the net load of the regional power grid, , These represent the regional load power and load dispatch power during time period t, respectively. , These represent the power output of photovoltaic and wind turbines in the region during time period t. The scheduling period; The constraints of the load dispatching model include: Power balance constraints ； In the above formula, , , These represent the power loss during time period t, the power purchased from the main grid, and the gas turbine power, respectively. Regional load dispatch power constraints ； In the above formula, This represents the maximum load dispatch power of the regional power grid.

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