Main grid-distribution grid-micro grid collaborative low carbon optimization dispatching control method based on coordination variable calculation

Abstract

This invention provides a method for coordinated low-carbon optimization scheduling and control of the main grid, distribution network, and microgrid based on coordination variable calculation, belonging to the technical field of coordinated low-carbon optimization scheduling and control of the main grid, distribution network, and microgrid. To maintain overall system coordination and reduce communication and computational pressure, a hierarchical optimization architecture is adopted. The main grid layer, distribution network layer, and microgrid layer respectively acquire the basic data required for coordinated scheduling. The main grid layer or distribution network layer calculates the node carbon factor of each microgrid access node based on the electricity carbon emission flow theory, and sends the node carbon factor, the main grid benchmark carbon factor, and the carbon price as low-carbon signals to the corresponding microgrid. i Each microgrid edge control node calculates the available energy storage based on the local energy storage state of charge and energy storage capacity. i Each microgrid calculates surplus photovoltaic power based on predicted photovoltaic output, local load, and rechargeable energy storage power; this invention is applied to grid-coordinated low-carbon optimization scheduling.

Description

Technical Field

[0001] This invention provides a method for coordinated low-carbon optimization scheduling and control of the main grid, distribution network, and microgrid based on the calculation of coordination variables, belonging to the technical field of coordinated low-carbon optimization scheduling and control of the main grid, distribution network, and microgrid. Background Technology

[0002] With the large-scale integration of new energy sources and the widespread application of distributed power sources, energy storage, and flexible loads on the distribution network side in recent years, the operation mode of the power system is gradually evolving from centralized dispatching of the main grid to multi-level collaborative operation of the main grid, distribution network, and microgrid. Under the background of "dual carbon" objectives, carbon emission constraints have been introduced into the power system operation and dispatch decision-making process, which has expanded the dispatch objectives from the traditional economic and security requirements to multi-objective collaborative optimization of economic, security, and low carbon requirements.

[0003] In existing research and engineering practice, the coordination between the main grid, distribution grid and microgrid mostly relies on interface-level power exchange or simple information interaction, lacking system design for the multi-level scheduling and control structure itself. Under carbon emission constraints, each level shows significant differences in decision-making objectives, constraints and information needs. Without a clear hierarchical division and coordination mechanism, problems such as difficulty in effectively transmitting carbon constraints, unclear coupling of scheduling objectives, and conflicts between distributed autonomy and centralized optimization will occur.

[0004] In traditional power systems, centralized dispatch has long been the dominant operating mode. This mode involves the main grid dispatch center acquiring system operation information and performing system-wide dispatch calculations within a unified optimization model. Centralized dispatch allows for the coordination of unit output, load demand, and network constraints across the entire system, thereby minimizing overall system operating costs and ensuring safe operation. However, with the large-scale integration of new energy sources and distributed resources, the operating structure of power systems is undergoing profound changes. The integration of numerous distributed photovoltaic systems, energy storage systems, electric vehicles, and flexible loads into the distribution network is causing the traditional power grid to gradually evolve into a new type of power system with a high degree of coupling between "source-grid-load-storage." At this point, if a completely centralized optimization dispatch is still adopted, the following engineering problems will arise:

[0005] Firstly, there is the challenge of information acquisition: In distribution networks and microgrids, a large number of distributed resources operate autonomously, and their internal operating status is typically managed by local control systems. The main grid dispatch center struggles to obtain all device-level information in real time. For example, information such as the state of charge of energy storage systems within microgrids, the real-time output of distributed power sources, and load response capabilities is often held by the local control system, rather than being fully transmitted to the main grid dispatch center. This incomplete information visibility makes it difficult for centralized optimization models to accurately describe the true operating status of the system.

[0006] Secondly, there is the problem of rapidly increasing computational scale: as the number of distributed resources increases, if centralized optimization is still used, the scheduling model needs to include a large number of device-level variables and constraints, leading to a rapid expansion of the optimization problem scale. When the system scale reaches thousands or even tens of thousands of controllable nodes, the computational complexity of centralized solutions will increase significantly, making it difficult to meet the computational speed requirements of real-time power system scheduling.

[0007] Finally, there is the issue of scheduling responsibility boundaries: In actual operation, the main grid dispatch center, distribution network dispatch center, and microgrid control system each undertake different management responsibilities. If all decisions are made centrally in the same dispatch center, it can easily lead to conflicts between dispatch authority and management boundaries. Summary of the Invention

[0008] To address the technical problems existing in the background art, the present invention adopts the following technical solution: a coordinated low-carbon optimization scheduling and control method for main grid-distribution network-microgrid based on coordination variable calculation, comprising the following scheduling and control steps:

[0009] Step S1: At the beginning of each scheduling cycle, the main network layer, distribution network layer, and microgrid layer respectively obtain the basic data required for coordinated scheduling, including:

[0010] Main network side data: The main network layer obtains the electricity purchase price λ. buy (t), Electricity sales price λ sell (t), Main grid reference carbon factor C base (t), carbon price λ c (t), Maximum power limit of main distribution switching P max GD (t), Lower limit of main distribution switching power P min GD (t);

[0011] Distribution network side data: The distribution network layer obtains the equivalent load P of the distribution network non-microgrid foundation. D,base (t), Distribution network loss power P loss,D (t), Maximum power P of each micro-interface max DM,i (t), lower power limit P of each micro-interface min DM,i (t), and the maximum allowable transmission power P of the inter-micronet mutual assistance channels. max line,ij (t);

[0012] Microgrid-side data: The microgrid layer obtains the predicted load power P of the i-th microgrid. L,i (t), Photovoltaic Predicted Output P PV,i (t), State of Charge (SOC) i (t), Rated energy storage capacity E iEnergy storage minimum state of charge (SOC) min i Energy storage maximum state of charge (SOC) max i Maximum charging power P of energy storage ch,max ESS,i (t), Maximum discharge power of energy storage P dis,max ESS,i (t);

[0013] Step S2: The main grid layer or distribution grid layer calculates the nodal carbon factor (CEF) of each microgrid access node based on the electricity carbon emission flow theory. i (t), and the nodal electrocarbon factor CEF i (t), Main grid reference carbon factor C base (t) and carbon price λ c (t) is sent to the corresponding microgrid as a low-carbon signal;

[0014] Step S3: The i-th microgrid edge control node calculates the available energy of energy storage based on the local energy storage state of charge and energy storage capacity; the i-th microgrid calculates the surplus photovoltaic power based on the predicted photovoltaic output, local load, and energy storage rechargeable power.

[0015] Step S4: The i-th microgrid calculates the autonomously optimized distribution micro-switching power plan based on the local load, photovoltaic, energy storage, and flexible load operating status;

[0016] Step S5: The i-th microgrid calculates the inter-microgrid coordination requirements based on local load, photovoltaic output, and energy storage discharge capacity, and further calculates the microgrid exchange capacity;

[0017] Step S6: After receiving the distribution network switching power plan reported by each microgrid, the distribution network layer calculates the main distribution switching power demand on the distribution network side by combining the distribution network basic load and distribution network loss.

[0018] Step S7: After receiving the main distribution switching power demand reported by the distribution network layer, the main network layer calculates the main distribution switching power plan based on the main distribution tie line capacity constraints.

[0019] Step S8: The distribution network layer calculates the main distribution power deviation based on the main distribution switching power plan issued by the main network layer, and allocates the main distribution power deviation according to the adjustable capability of each microgrid to obtain the distribution-micro switching power boundary of the i-th microgrid.

[0020] Step S9: The distribution network layer calculates the inter-micronetwork switching power plan in a unified manner based on the inter-micronetwork coordination requirements and switching capabilities reported by each micronetwork.

[0021] Step S10: After the distribution network layer forms the distribution micro-grid switching power and the microgrid inter-grid switching power, it performs a safety check on the distribution network operation status and issues control boundaries, including node voltage check and line capacity check.

[0022] Step S11: The i-th microgrid adjusts its local energy storage charging and discharging, flexible load, and photovoltaic consumption strategies to ensure that the actual distribution microgrid switching power tracks the distribution microgrid switching power boundary issued by the distribution grid layer and feeds back the actual power.

[0023] Step S12: The distribution network layer summarizes the execution deviations of each microgrid, calculates the total deviation for the region, and performs rolling feedback correction.

[0024] The specific method for step S2 is as follows:

[0025] The nodal electrocarbon factor is calculated based on the nodal carbon flux balance relationship, and the calculation formula is as follows:

[0026] ;

[0027] Among them, CEF i (t) represents the node carbon factor of the i-th microgrid access node at time t; P out i (t) represents the outflow power or equivalent supply power of node i at time t; Ω in i Represents the set of upstream nodes that inject power into node i; CEF k (t) represents the nodal carbon factor of upstream node k at time t; P ki (t) represents the active power transmitted from node k to node i; G i Represents the set of local power sources for access node i; η g P represents the carbon emission coefficient per unit of electricity generated by the g-th local power source; g,i (t) represents the active power output of the g-th local power source at node i; when node i has no local power source. Take zero.

[0028] The specific method for step S3 is as follows:

[0029] The i-th microgrid edge control node calculates the available energy E of the energy storage based on the local energy storage state of charge and energy storage capacity. ava ESS,i (t), the calculation formula is:

[0030] ;

[0031] Among them, E ava ESS,i (t) represents the energy that the i-th microgrid energy storage can still release after satisfying the minimum state of charge constraint at time t; SOC i (t) represents the state of charge (SOC) of the i-th microgrid energy storage at time t; min iE represents the minimum allowable state of charge for the i-th microgrid energy storage; i This represents the rated energy storage capacity of the i-th microgrid;

[0032] The i-th microgrid further calculates the energy storage charging power used for photovoltaic power consumption, using the following formula:

[0033] ;

[0034] Among them, P ava,ch ESS,i (t) represents the charging power that the i-th microgrid energy storage can absorb from photovoltaics at time t; P ch ,max ESS,i Represents the maximum charging power of the i-th microgrid energy storage; SOC max i The maximum state of charge allowed for the i-th microgrid energy storage is represented by Δt; Δt represents the time interval between two adjacent scheduling moments.

[0035] The i-th microgrid calculates its surplus photovoltaic power based on the predicted photovoltaic output, local load, and rechargeable energy storage power. The calculation formula is as follows:

[0036] ;

[0037] Among them, P sur PV,i (t) represents the surplus photovoltaic power of the i-th microgrid at time t; P PV,i (t) represents the predicted photovoltaic output of the i-th microgrid at time t; P L,i (t) represents the predicted load power of the i-th microgrid at time t.

[0038] The specific method for step S4 is as follows:

[0039] The i-th microgrid calculates the autonomous optimization-based distribution-microgrid switching power plan P based on the operating status of local load, photovoltaic, energy storage, and flexible load. plan DM,i (t), the calculation formula is:

[0040] ;

[0041] Among them, P plan DM,i (t) represents the distribution-micro-switching power plan formed by the i-th microgrid autonomous optimization; P ch ESS,i (t) represents the charging power of the i-th microgrid energy storage at time t; P dis ESS,i (t) represents the discharge power of the i-th microgrid energy storage at time t; P inc FL,i(t) represents the increase in power of the i-th microgrid flexible load at time t; P dec FL,i (t) represents the power reduction of the i-th microgrid flexible load at time t;

[0042] When P plan DM,i When (t)>0, it means that the i-th microgrid plans to purchase electricity from the distribution network;

[0043] When P plan DM,i When (t) < 0, it means that the i-th microgrid plans to send power to the distribution network.

[0044] The specific method for step S5 is as follows:

[0045] The i-th microgrid calculates the inter-microgrid coordination demand P based on local load, photovoltaic output, and energy storage discharge capacity. req MG,i (t):

[0046] First, calculate the discharge power of the stored energy. The calculation formula is as follows:

[0047] ;

[0048] Among them, P ava,dis ESS,i (t) represents the power of the i-th microgrid energy storage available for discharge support at time t; P dis ,max ESS,i (t) represents the maximum discharge power of the i-th microgrid energy storage;

[0049] Then, the inter-microgrid collaboration requirements are calculated using the following formula:

[0050] ;

[0051] Among them, P req MG,i (t) represents the power demand that the i-th microgrid needs to be supported by other microgrids when the local photovoltaic and energy storage discharge capacity is insufficient to meet the load.

[0052] Further calculations of the microgrid's switchable capacity are performed using the following formula:

[0053] ;

[0054] Among them, P max MG,i (t) represents the maximum mutual power that the i-th microgrid can provide to other microgrids at time t.

[0055] The specific method for step S6 is as follows:

[0056] Calculate the main distribution switching power demand P on the distribution network side. req GM,i (t), the calculation formula is:

[0057] ;

[0058] Among them, P req GM (t) represents the main distribution switching power demand reported by the distribution network layer to the main network layer; P D,base (t) represents the basic equivalent load power within the distribution network area excluding microgrids; N represents the number of microgrids;

[0059] P loss,D (t) represents the power loss of the distribution network, which is specifically obtained through distribution network power flow calculation. The calculation formula is as follows:

[0060] ;

[0061] Among them, L D Represents the set of distribution network lines; r1 represents the resistance of the l-th distribution line; I l (t) represents the current of the l-th distribution line at time t.

[0062] The specific method for step S7 is as follows:

[0063] The main network layer receives the P reported by the distribution network layer. req GM After (t), calculate the planned main and distribution switching power P based on the main and distribution tie line capacity constraints. GD (t), the calculation formula is:

[0064] ;

[0065] Among them, P GD (t) represents the main distribution switching power plan issued from the main network layer to the distribution network layer; P max GD (t) represents the upper limit of the main distribution switching power; P min GD (t) represents the lower limit of the main distribution network's switching power; when the distribution network is allowed to feed back power to the main network, P max GD (t) takes a negative value.

[0066] The specific method for step S8 is as follows:

[0067] The distribution network layer uses the P issued by the main network layer. GD (t), calculate the main distribution power deviation, the calculation formula is:

[0068] ;

[0069] Where, ΔP D (t) represents the deviation between the main power switching plan issued by the main grid and the original power demand on the distribution network side;

[0070] The distribution network layer adjusts ΔP based on the adjustability of each microgrid. D (t) is used for allocation to obtain the distribution-micro-switching power boundary of the i-th microgrid. The calculation formula is as follows:

[0071] ;

[0072] Among them, P DM,i (t) represents the distribution-micro-switching power boundary sent from the distribution network layer to the i-th microgrid;

[0073] α i (t) represents the allocation coefficient for the main distribution power deviation correction undertaken by the i-th microgrid, and the calculation formula is:

[0074] ;

[0075] Among them, A i (t) represents the adjustability of the i-th microgrid at time t; A k (t) represents the adjustability of the k-th microgrid at time t;

[0076] The adjustability A of the i-th microgrid i The formula for calculating (t) is:

[0077] ;

[0078] Among them, P inc,max FL,i P represents the maximum increase in power that the i-th microgrid flexible load can achieve; dec,max FL,i This indicates the maximum power reduction that can be achieved by the flexible load of the i-th microgrid.

[0079] The power boundary of the microswitch is satisfied as follows:

[0080] ;

[0081] Among them, P min DM,i (t) represents the lower limit of the power of the i-th microgrid distribution microswitch; P max DM,i (t) represents the upper limit of the power of the i-th microgrid distribution microswitch.

[0082] The specific method for step S9 is as follows:

[0083] The distribution network layer bases its work on the inter-micronetwork coordination requirements reported by each micronetwork. req MG,i(t) and exchangeability P max MG,i (t), unified calculation of inter-microgrid switching power plan:

[0084] When the i-th microgrid has exchangeable capacity and the j-th microgrid has coordination needs, the distribution network layer calculates the planned exchange power from microgrid i to microgrid j using the following formula:

[0085] ;

[0086] Among them, P MG,ij (t) represents the power exchange plan between microgrid i and microgrid j; P max MG,i (t) represents the maximum mutual support power that microgrid i can provide to other microgrids; P req MG,j (t) represents the power requirement of microgrid j that it needs to support from other microgrids; P max line,ij (t) represents the maximum allowable transmission power when power mutual assistance is achieved between microgrid i and microgrid j through the distribution network channel;

[0087] The switching power between microgrids satisfies an antisymmetric relationship:

[0088] ;

[0089] Among them, P MG,ij (t)>0 indicates that microgrid i supplies power to microgrid j, P MG,ij (t) < 0 indicates that microgrid j supplies power to microgrid i.

[0090] The specific method for step S10 is as follows:

[0091] In the formation of P DM,i (t) and P MG,ij After (t), a safety check is performed on the distribution network operation status, including node voltage check and line capacity check, which respectively meet the constraints:

[0092] ;

[0093] ;

[0094] Among them, V n (t) represents the voltage of distribution network node n at time t; V min n and V max n S represents the lower and upper voltage limits of node n, respectively; l (t) represents the apparent power of the l-th distribution line at time t; S max lThis indicates the maximum permissible apparent power of the l-th distribution line;

[0095] If the security check meets the constraints, the distribution network layer sends P to each microgrid. DM,i (t), P MG,ij (t), λ buy (t), λ sell (t), CEF i (t) and λ c (t);

[0096] If the security check does not meet the constraints, the distribution network layer returns to steps S8 and S9 to readjust the distribution micro-switching power boundary and the inter-micro-network switching power plan.

[0097] The present invention has the following advantages over the prior art:

[0098] I. This invention constructs a three-tiered control architecture of "main grid coordination, distribution network coordination, and microgrid autonomy," which clarifies the functional and decision-making boundaries of the main grid layer, distribution network layer, and microgrid layer, thus avoiding the problem of conflict between scheduling authority and management boundaries in traditional centralized scheduling.

[0099] Second, this invention achieves cross-level power coordination through power coordination variables such as main distribution switching power, distribution micro-switching power, and micro-network inter-switching power. Only a small number of boundary coordination variables are exchanged between each level, and it is not necessary to upload all device-level information, which can reduce communication pressure and centralized computing pressure.

[0100] Third, this invention further introduces power purchase and sale price, nodal carbon factor, carbon price and state / capacity support variables on the basis of power coordination variables, so that the hierarchical control architecture has the expansion capabilities of economic operation, low-carbon operation and multi-microgrid mutual assistance.

[0101] Fourth, this invention achieves the downward decomposition of system-level optimization goals and the upward feedback of local operating status through a closed-loop control process of "bottom-up demand formation, top-down boundary issuance, and rolling feedback correction," taking into account both overall system coordination and microgrid local autonomy.

[0102] Fifth, this invention organizes mutual assistance between microgrids in a unified manner through the distribution network layer, and forms a power exchange plan between microgrids by combining regional network security verification, thereby avoiding the operational risks caused by disordered point-to-point interaction between multiple microgrids and improving the efficiency of regional resource utilization and the capacity for new energy consumption.

[0103] VI. This invention establishes a coordination variable communication connection mechanism, multi-source data interaction and interface standards, and a scheduling control command priority mechanism, enabling the main-distribution-micro collaborative control architecture to have engineering implementation conditions and operational reliability. Detailed Implementation

[0104] This invention provides a low-carbon optimization scheduling and control method based on the calculation of coordination variables among the main grid, distribution network, and microgrid. From an engineering implementation perspective, it proposes to construct a multi-level collaborative scheduling and control architecture among the main grid, distribution network, and microgrid. This architecture structurally decomposes the traditional centralized optimization problem into layers, with the main grid responsible for system-level balance and global constraint management, the distribution network responsible for regional network security and resource coordination, and the microgrid or power grid conducting autonomous optimization based on local information. Cross-layer collaboration is achieved through a small number of boundary exchange variables. Compared to completely centralized scheduling, the layered optimization architecture adopted in this invention can maintain overall system coordination while significantly reducing communication and computing pressure, which is more in line with the actual situation of highly dispersed distributed resources and diversified operating entities in the distribution network.

[0105] To adapt to the development trend of high-proportion distributed resource access in new power systems and fully leverage the operational and management advantages of different levels of the main grid, distribution network, and microgrid, this invention constructs a coordinated control architecture for the main grid, distribution network, and microgrid to achieve coordinated, low-carbon, and optimized scheduling. This architecture consists of three levels: the main grid scheduling layer, the distribution network coordination layer, and the microgrid autonomy layer. Specifically, the main grid layer is responsible for system-level operational coordination and global optimization decisions; the distribution network layer is responsible for regional resource coordination and network operation management; and the microgrid layer is responsible for local source-load-storage resource autonomous optimization. While maintaining relatively independent decision-making capabilities, each level achieves cross-level coordinated operation through unified coordination variables and information interaction mechanisms, thereby forming a centralized-distributed hybrid control architecture that balances overall system optimization with rapid local response capabilities.

[0106] In this architecture, the main grid scheduling layer is located at the top of the system control hierarchy, primarily conducting coordination and decision-making from the perspective of overall system operation. The main grid layer is responsible for formulating power exchange plans for main and distribution grids and managing system-level operational targets, providing boundary operating conditions and coordination basis for the distribution grid layer. The main grid layer does not directly participate in power flow control within the distribution grid or resource optimization of source, load, and storage within microgrids; instead, it achieves collaborative operation with lower-level control layers through coordination variables. The distribution grid coordination layer, located between the main grid layer and the microgrid layer, is a crucial hub connecting system-level control and edge autonomous control. The distribution grid layer is responsible for the convergence and coordination of the operating status of multiple microgrids within the region, decomposing the scheduling plans issued by the main grid, and conducting coordinated control in conjunction with regional network operating constraints. Simultaneously, the distribution grid layer also undertakes regional operational safety verification functions, realizing coordinated management of main and distribution grid power exchange and distribution-microgrid power exchange to ensure the safe and stable operation of the regional power grid. The microgrid autonomous layer is located at the bottom of the control hierarchy and consists of multiple microgrid edge control nodes. Each microgrid conducts autonomous optimization based on the operating status of local photovoltaic, energy storage, and flexible load resources, forming an external power exchange plan while meeting local operational needs. Through edge autonomous control mechanisms, microgrids can quickly respond to changes in local operating status, improving the overall operational flexibility of the system.

[0107] In order to achieve coordinated operation between different levels, the present invention establishes a unified information interaction system in the main network-distribution network-microgrid control architecture. Based on the future operating characteristics of active distribution networks and the requirements for low-carbon operation, this invention classifies the information transmitted during the main grid-distribution network-microgrid coordination process into four categories: power flow, status flow, price flow, and low-carbon signal flow. Specifically: power flow describes the energy exchange relationships between different levels, including the main grid-distribution network power exchange and the distribution network-microgrid power exchange, serving as crucial coordination information for achieving system power balance; status flow reflects the operating status of resources at each level, including load forecasting information, renewable energy output forecasting information, energy storage charge status, and adjustable resource capacity, providing fundamental data support for collaborative decision-making; price flow primarily transmits market operation information, including electricity purchase price, electricity sales price, and market transaction information, providing a basis for economic dispatch decisions at each level; and low-carbon signal flow supports the collaborative control requirements under future low-carbon operation goals, including node carbon factors, carbon prices, and low-carbon operation constraints. By reserving a low-carbon signal interaction interface, the constructed main grid-distribution network-microgrid collaborative control architecture can provide unified architectural support for subsequent research on low-carbon dispatch control strategies.

[0108] From the perspective of the operation mechanism, this invention adopts a collaborative control mode of global coordination, regional coordination, and local autonomy. The main network layer is responsible for overall planning of global operation goals, the distribution network layer is responsible for regional coordination and constraint management, and the microgrid layer is responsible for local resource autonomous optimization. Through information interaction and coordination variable transmission between levels, the system-level optimization goals are decomposed downward and the local operation status is fed back upward, ultimately forming a multi-level collaborative operation closed loop.

[0109] The main grid, distribution, and microgrid collaborative control system provided by this invention has different control objects and decision-making responsibilities at each level of control unit. The main grid layer focuses on the overall system operation status, the distribution grid layer focuses on regional network operation security and resource coordination, and the microgrid layer focuses on local source-load-storage resource autonomous optimization. To avoid decision duplication, control conflicts, and information redundancy between different levels, it is necessary to clarify the decision boundaries of each level. Based on the requirements of main grid, distribution, and microgrid collaborative control, a multi-dimensional coordination variable system composed of power coordination variables, price coordination variables, and low-carbon coordination variables is constructed to achieve information interaction and collaborative control between different levels.

[0110] (1) Decision boundary:

[0111] The main grid layer adopts a hierarchical decision-making model of "global coordination, regional coordination, and local autonomy." Each layer is only responsible for optimization decisions within its control scope and achieves cross-layer collaboration through a limited number of coordination variables. The main grid layer is mainly responsible for setting system-level operational goals and coordinating main and distribution switching power, and does not directly participate in power flow management within the distribution network or equipment control within the microgrid. The distribution network layer is mainly responsible for regional operational coordination and network security management, and does not directly participate in the optimization of source, load, and storage equipment within the microgrid. The microgrid layer is responsible for local resource autonomous control and does not participate in system-level operational decisions.

[0112] By defining the boundaries as described above, complex large-scale optimization problems can be decomposed into multiple hierarchical sub-problems, achieving a control mode that combines global coordination with local autonomy. Based on these principles, information interaction between the main network layer, distribution network layer, and microgrid layer is primarily accomplished through coordination variables. These coordination variables serve as both the carrier of information exchange between different levels and a crucial link in achieving collaborative optimization.

[0113] (2) Power coordination variables:

[0114] Power coordination variables are used to describe the energy exchange relationship between different levels and are the most crucial coordination variables in the main grid-distribution micro-coordinated control process. Between the main grid layer and the distribution grid layer, the main grid-distribution exchange power P is introduced. GD (t) represents the amount of active power exchanged between the main grid and the distribution grid. When P GD When (t) > 0, it indicates that the main grid supplies power to the distribution network; when P GD When (t) < 0, it indicates that the distribution network is feeding power back to the main network. A distribution-microgrid switching power P is introduced between the distribution network layer and the microgrid layer. DM,i (t) represents the power exchange between the i-th microgrid and the distribution network. When P DM,i When (t) > 0, it indicates that the microgrid purchases electricity from the distribution network; when P DM,i When (t) < 0, it indicates that the microgrid is supplying power to the distribution network. For multi-microgrid collaborative scenarios, the inter-microgrid power exchange P can be further introduced. MG,ij (t) is used to describe the power exchange relationship between microgrid i and microgrid j, thereby supporting resource sharing and collaborative operation among multiple microgrids. The power coordination variable constitutes the basis of energy interaction in the master-distributor-microgrid collaborative control system.

[0115] (3) Price coordination variables:

[0116] With the development of market mechanisms and demand response technologies, price signals have gradually become an important means of guiding user-side resources to participate in collaborative operations. Therefore, a price coordination variable interface is reserved in the master-slave micro-collaborative control architecture. The price coordination variables mainly include:

[0117] Electricity purchase price λ buy(t) is used to characterize the cost of electricity purchased by the microgrid from the upper-level grid;

[0118] Electricity price λ sell (t) is used to characterize the revenue obtained by the microgrid from selling electricity to the upper-level grid.

[0119] Price variables are primarily passed down from higher to lower levels, providing a basis for economic dispatch decisions at each level. In subsequent collaborative optimization, price coordination variables can guide microgrids in energy storage charging and discharging control, distributed power output coordination, and power purchase and sale strategy optimization, thereby improving the overall economic operation level of the system.

[0120] (4) Carbon coordination variables:

[0121] Under the "dual carbon" objective, the operational goals of power systems are gradually shifting from purely economic operation to the coordinated optimization of economy, safety, and low carbon emissions. Therefore, the main-distribution-micro-coordinated control system needs to possess low-carbon information exchange capabilities. To support subsequent low-carbon coordinated control requirements, this invention reserves low-carbon coordination variable interfaces in the main-distribution-micro-coordinated architecture, mainly including:

[0122] Node electrocarbon factor C EF,i (t) is used to characterize the carbon emission level corresponding to a unit of electricity consumption at a node;

[0123] Carbon price signal λ c (t) is used to characterize the economic cost corresponding to a unit of carbon emissions.

[0124] Low-carbon coordination variables are mainly passed from higher to lower levels, providing a basis for decision-making in subsequent low-carbon scheduling and low-carbon demand response.

[0125] It should be noted that power coordination variables, price coordination variables, and carbon coordination variables are the core boundary interaction variables in the main distribution microgrid coordinated control; state / capacity support variables mainly come from the microgrid autonomous optimization results and are used to assist the distribution network layer in judging the feasibility of mutual assistance between microgrids and regional coordination capabilities; load forecasting, photovoltaic forecasting, and SOC are operating status data, mainly used for microgrid autonomous optimization, and are not used as core boundary coordination variables between the main distribution microgrid and distribution levels. By establishing a unified coordination variable system, control units at different levels can achieve coordinated operation while maintaining their autonomous capabilities, providing a foundation for the design of subsequent parameter interaction mechanisms and the construction of hierarchical scheduling control processes.

[0126] In the main-distribution-microgrid coordinated control system, each level exchanges only a small number of boundary coordination variables, without exchanging internal optimization process information. The main grid layer coordinates with the distribution grid layer primarily through power exchange between the main and distribution grids; the distribution grid layer coordinates with the microgrid layer through power exchange between the distribution and microgrids; and microgrids achieve resource sharing through power exchange among themselves. Price and carbon variables, as extended coordination variables, can be used to support subsequent economic and low-carbon optimization decisions.

[0127] The present invention provides a coordinated low-carbon optimization scheduling and control method for the main grid, distribution network, and microgrid based on coordination variable calculation. This method is executed in a rolling manner according to the scheduling cycle. Let the discrete time within the scheduling cycle be t, the microgrid numbers be i and j, the total number of microgrids be N, and the main grid-distribution network switching power be P. GD (t) > 0 indicates that the main grid supplies power to the distribution network; the distribution micro-switching power P DM,i (t) > 0 indicates that the i-th microgrid purchases electricity from the distribution network; the power exchanged between microgrids is P. MG,ij (t)>0 indicates that microgrid i supplies power to microgrid j.

[0128] Step S1: Obtain basic data for primary-secondary-micro collaborative scheduling:

[0129] At the start of each scheduling cycle, the main network layer, distribution network layer, and microgrid layer respectively obtain the basic data required for coordinated scheduling, including:

[0130] (1) Main grid side data: The main grid layer obtains the electricity purchase price λ. buy (t), Electricity sales price λ sell (t), Main grid reference carbon factor C base (t), carbon price λ c (t), Maximum power limit of main distribution switching P max GD (t) and the lower limit of main distribution switching power P min GD (t).

[0131] (2) Distribution network side data: The distribution network layer obtains the equivalent load P of the distribution network non-microgrid foundation. D,base (t), Distribution network loss power P loss,D (t), Maximum power P of each micro-interface max DM,i (t), lower power limit P of each micro-interface min DM,i (t), and the maximum allowable transmission power P of the inter-micronet mutual assistance channels. max line,ij (t).

[0132] (3) Microgrid side data: The microgrid layer obtains the predicted load power P of the i-th microgrid. L,i (t), Photovoltaic Predicted Output P PV,i (t), State of Charge (SOC) i (t), Rated energy storage capacity E i Energy storage minimum state of charge (SOC) min i Energy storage maximum state of charge (SOC) max i Maximum charging power P of energy storage ch,maxESS,i (t), Maximum discharge power of energy storage P dis,max ESS,i (t).

[0133] Step S2: Calculate the node electrocarbon factor and issue a low-carbon signal:

[0134] The main grid layer or distribution grid layer calculates the nodal carbon emission factor (CEF) of each microgrid access node based on the theory of carbon emission flow in electricity. i (t), and CEF i (t), C base (t) and λ c (t) is sent to the corresponding microgrid as a low-carbon signal.

[0135] The nodal electrocarbon factor can be calculated based on the nodal carbon flux balance relationship:

[0136] ;

[0137] Among them, CEF i (t) represents the node carbon factor of the i-th microgrid access node at time t; P out i (t) represents the outflow power or equivalent supply power of node i at time t; Ω in i Represents the set of upstream nodes that inject power into node i; CEF k (t) represents the nodal carbon factor of upstream node k at time t; P ki (t) represents the active power transmitted from node k to node i; G i Represents the set of local power sources for access node i; η g P represents the carbon emission coefficient per unit of electricity generated by the g-th local power source; g,i (t) represents the active power output of the g-th local power source at node i. When node i has no local power source, Take zero.

[0138] Step S3: Calculate the available energy and surplus photovoltaic power of the microgrid layer:

[0139] The i-th microgrid edge control node calculates the available energy E of the energy storage based on the local energy storage state of charge and energy storage capacity. ava ESS,i (t):

[0140] ;

[0141] Among them, E ava ESS,i (t) represents the energy that the i-th microgrid energy storage can still release after satisfying the minimum state of charge constraint at time t; SOC i(t) represents the state of charge (SOC) of the i-th microgrid energy storage at time t; min i E represents the minimum allowable state of charge for the i-th microgrid energy storage; i This represents the rated energy storage capacity of the i-th microgrid.

[0142] The i-th microgrid further calculates the energy storage charging power available for photovoltaic absorption:

[0143] ;

[0144] Among them, P ava,ch ESS,i (t) represents the charging power that the i-th microgrid energy storage can absorb from photovoltaics at time t; P ch ,max ESS,i Represents the maximum charging power of the i-th microgrid energy storage; SOC max i Δt represents the maximum allowable state of charge for the i-th microgrid energy storage; Δt represents the time interval between two adjacent scheduling moments.

[0145] The i-th microgrid calculates its surplus photovoltaic power based on the predicted photovoltaic output, local load, and rechargeable energy storage power:

[0146] ;

[0147] Among them, P sur PV,i (t) represents the surplus photovoltaic power of the i-th microgrid at time t; P PV,i (t) represents the predicted photovoltaic output of the i-th microgrid at time t; P L,i (t) represents the predicted load power of the i-th microgrid at time t.

[0148] Step S4: Calculate the power allocation plan for micro-switches at the microgrid layer:

[0149] The i-th microgrid calculates the autonomous optimization-based distribution-microgrid switching power plan P based on the operating status of local load, photovoltaic, energy storage, and flexible load. plan DM,i (t):

[0150] ;

[0151] Among them, P plan DM,i (t) represents the distribution-micro-switching power plan formed by the i-th microgrid autonomous optimization; P ch ESS,i (t) represents the charging power of the i-th microgrid energy storage at time t; P dis ESS,i(t) represents the discharge power of the i-th microgrid energy storage at time t; P inc FL,i (t) represents the increase in power of the i-th microgrid flexible load at time t; P dec FL,i (t) represents the power reduction of the i-th microgrid flexible load at time t.

[0152] When P plan DM,i When (t)>0, it means that the i-th microgrid plans to purchase electricity from the distribution network; when P plan DM,i When (t) < 0, it means that the i-th microgrid plans to send power to the distribution network.

[0153] Step S5: Microgrid layer calculates inter-microgrid collaboration requirements and exchange capabilities:

[0154] The i-th microgrid calculates the inter-microgrid coordination demand P based on local load, photovoltaic output, and energy storage discharge capacity. req MG,i (t). First, calculate the dischargeable power of the stored energy:

[0155] ;

[0156] Among them, P ava,dis ESS,i (t) represents the power of the i-th microgrid energy storage available for discharge support at time t; P dis ,max ESS,i (t) represents the maximum discharge power of the i-th microgrid energy storage.

[0157] Then calculate the inter-micronet collaboration requirements:

[0158] ;

[0159] Among them, P req MG,i (t) represents the power demand that the i-th microgrid needs to be supported by other microgrids when the local photovoltaic and energy storage discharge capacity is insufficient to meet the load.

[0160] Further calculation of the microgrid's switchable capacity:

[0161] ;

[0162] Among them, P max MG,i (t) represents the maximum mutual power that the i-th microgrid can provide to other microgrids at time t.

[0163] The i-th micronet will P plan DM,i (t), Preq MG,i (t), P max MG,i (t), P sur PV,i (t) and E ava ESS,i (t) are reported to the distribution network layer.

[0164] Step S6: The distribution network layer calculates the main-distribution exchange power demand:

[0165] After receiving the distribution-microgrid exchange power plans reported by each microgrid, the distribution network layer calculates the main-distribution exchange power demand P on the distribution network side in combination with the distribution network base load and the distribution network power loss req GM,i (t):

[0166] ;

[0167] Herein, P req GM (t) represents the main-distribution exchange power demand reported by the distribution network layer to the main grid layer; P D,base (t) represents the base equivalent load power excluding microgrids in the distribution network area; N represents the number of microgrids; P loss,D (t) represents the distribution network power loss.

[0168] The distribution network power loss can be obtained through distribution network power flow calculation, and can also be calculated approximately according to the line loss:

[0169] ;

[0170] Herein, L D represents the set of distribution network lines; r1 represents the resistance of the l-th distribution line; I l (t) represents the current of the l-th distribution line at time t.

[0171] The distribution network layer transmits P req GM (t) to the main grid layer.

[0172] Step S7: The main grid layer calculates and issues the main-distribution exchange power plan:

[0173] After receiving P reported by the distribution network layer req GM (t), the main grid layer calculates the main-distribution exchange power plan P according to the capacity constraint of the main-distribution tie line GD (t):

[0174] ;

[0175] Herein, P GD (t) represents the main-distribution exchange power plan issued by the main grid layer to the distribution network layer; Pmax GD (t) represents the upper limit of the main distribution switching power; P min GD (t) represents the lower limit of the main distribution network's switching power. When the distribution network is allowed to feed back power to the main network, P max GD (t) can take negative values.

[0176] The main network layer will P GD (t), λ buy (t), λ sell (t), C base (t) and λ c (t) is sent to the distribution network layer. Where λ buy (t), λ sell (t), C base (t) and λ c (t) is directly sent as an input signal, and its calculation method is not limited in this method.

[0177] Step S8: Calculate the power boundary of the distribution network micro-switches at the distribution network layer:

[0178] The distribution network layer uses the P issued by the main network layer. GD (t), calculate the main distribution power deviation:

[0179] ;

[0180] Where, ΔP D (t) represents the deviation between the main power switching plan issued by the main grid and the original power demand on the distribution network side.

[0181] The distribution network layer adjusts ΔP based on the adjustability of each microgrid. D (t) is used for allocation to obtain the distribution-micro-switching power boundary of the i-th microgrid:

[0182] ;

[0183] Among them, P DM,i (t) represents the distribution-micro-switching power boundary sent from the distribution network layer to the i-th microgrid; α i (t) represents the allocation coefficient for the main and distribution power deviation correction undertaken by the i-th microgrid.

[0184] Distribution coefficient α i (t) is calculated using the following formula:

[0185] ;

[0186] Among them, A i (t) represents the adjustability of the i-th microgrid at time t; A k (t) represents the adjustability of the k-th microgrid at time t.

[0187] The adjustability A of the i-th microgrid i (t) can be calculated using the following formula:

[0188] ;

[0189] Among them, P inc,max FL,i P represents the maximum increase in power that the i-th microgrid flexible load can achieve; dec,max FL,i This indicates the maximum power reduction that can be achieved by the flexible load of the i-th microgrid.

[0190] The power boundary of the microswitch is satisfied as follows:

[0191] ;

[0192] Among them, P min DM,i (t) represents the lower limit of the power of the i-th microgrid distribution microswitch; P max DM,i (t) represents the upper limit of the power of the i-th microgrid distribution microswitch.

[0193] Step S9: Calculate the inter-microgrid switching power plan at the distribution network layer:

[0194] The distribution network layer bases its work on the inter-micronetwork coordination requirements reported by each micronetwork. req MG,i (t) and exchangeability P max MG,i (t), to uniformly calculate the power exchange plan between microgrids.

[0195] When the i-th microgrid has exchangeable capabilities and the j-th microgrid has collaborative needs, the distribution network layer calculates the microgrid. Power switching plan for microgrid j:

[0196] ;

[0197] Among them, P MG,ij (t) represents the power exchange plan between microgrid i and microgrid j; P max MG,i (t) represents the maximum mutual support power that microgrid i can provide to other microgrids; P req MG,j (t) represents the power requirement of microgrid j that it needs to support from other microgrids; P max line,ij (t) represents the maximum allowable transmission power when power exchange is achieved between microgrid i and microgrid j through the distribution network channel.

[0198] The switching power between microgrids satisfies an antisymmetric relationship:

[0199] ;

[0200] Among them, P MG,ij (t)>0 indicates that microgrid i supplies power to microgrid j, P MG,ij (t) < 0 indicates that microgrid j supplies power to microgrid i.

[0201] The distribution network layer will P MG,ij (t) Issued to relevant microgrids to guide them in carrying out energy sharing under the unified organization and security verification of the distribution network layer.

[0202] Step S10: The distribution network layer performs operational security verification and issues control boundaries:

[0203] In the formation of P DM,i (t) and P MG,ij After (t), a safety check is performed on the distribution network operation status. The safety check includes node voltage check and line capacity check:

[0204] ;

[0205] ;

[0206] Among them, V n (t) represents the voltage of distribution network node n at time t; V min n and V max n S represents the lower and upper voltage limits of node n, respectively; l (t) represents the apparent power of the l-th distribution line at time t; S max l This indicates the maximum allowable apparent power of the l-th distribution line.

[0207] If the security check meets the constraints, the distribution network layer sends P to each microgrid. DM,i (t), P MG,ij (t), λ buy (t), λ sell (t), CEF i (t) and λ c (t). If the security check does not meet the constraints, the distribution network layer returns to S8 and S9 to readjust the distribution micro-switching power boundary and the inter-micro-network switching power plan.

[0208] Step S11: The microgrid layer performs control and feeds back the actual power:

[0209] The i-th microgrid receives P from the distribution network layer. DM,i (t), P MG,ij (t), λ buy (t), λsell (t), CEF i (t) and λ c After (t), adjust the local energy storage charging and discharging, flexible load and photovoltaic consumption strategies to make the actual distribution micro-switching power track the distribution micro-switching power boundary issued by the distribution network layer.

[0210] After the i-th microgrid executes, it feeds back the actual microgrid-distribution switching power P to the distribution network layer. act DM,i (t), and calculate the execution deviation:

[0211] ;

[0212] Among them, P act DM,i (t) represents the actual micro-switching power of the i-th microgrid after the control is executed; ΔP DM，i (t) represents the deviation between the actual execution result of the i-th microgrid and the distribution network boundary.

[0213] Step S12: The distribution network layer performs rolling feedback correction:

[0214] The distribution network layer summarizes the execution deviations of each microgrid and calculates the total deviation for the region:

[0215] ;

[0216] Where, ΔP act D (t) represents the sum of the power execution deviations of each microgrid and microswitch within the distribution network area.

[0217] like Then the primary-secondary-micro collaborative low-carbon optimization scheduling for the current scheduling cycle is completed; if Then the distribution network layer recalculates P based on the latest feedback data. DM,i (t) and P MG,ij (t), if necessary, resubmit the corrected P to the main network layer. req GM (t), and then proceed to the next round of rolling optimization. Where, ε D This indicates the allowable power deviation threshold for the distribution network area.

[0218] In a master-distributor-microgrid coordinated control system, coordination variables are the core carriers for achieving coordinated operation between different levels. The optimization scheduling method provided in this invention classifies coordination variables into types such as power coordination variables, price coordination variables, carbon coordination variables, and state / capacity support variables. Among them, power coordination variables are used to describe the energy exchange relationship between levels, price coordination variables are used to guide economic operation, carbon coordination variables are used to support low-carbon operation, and state / capacity support variables are used to reflect the ability of microgrids to participate in regional coordination and mutual assistance among microgrids.

[0219] To ensure that the above variables can play their role in actual operation, it is also necessary to establish a corresponding operational support mechanism, including the following steps:

[0220] First, power coordination variables need to meet the requirements for safe operation of the power grid. Main and distribution switching power P GD (t), the micro-switching power PDM,i(t) and the inter-microgrid switching power P MG,ij (t) Although formed by optimization or coordination at various levels, its corresponding operating state must meet the physical constraints of the power grid. Therefore, before executing the power coordination variables, it is necessary to conduct an operational verification based on the power grid topology, line parameters, node parameters, and equipment capacity to determine whether they will cause problems such as node voltage exceeding limits, line power flow exceeding limits, or equipment capacity exceeding limits. If the operating state corresponding to the power coordination variables meets the safety constraints, it can proceed to the execution stage; if there is a risk of exceeding limits, it is necessary to return to the corresponding coordination layer for correction.

[0221] Secondly, the price coordination variables need to be compatible with the microgrid's autonomous optimization process. Electricity purchase price λ buy (t) and electricity price λ sell (t) is mainly used to guide microgrids in selecting operating modes such as electricity purchase, electricity sale, energy storage charging and discharging, and distributed power generation output coordination at different time periods. Price signals themselves do not directly change the system power flow, but they do affect the microgrid's autonomous optimization results, and thus affect the power exchange between distribution and microgrids and the power exchange between microgrids. Therefore, in the operation support mechanism, price variables mainly serve as external input signals for microgrid optimization decisions.

[0222] Furthermore, carbon coordination variables need to be aligned with low-carbon operation goals. Node-specific carbon factor C EF,i (t) and carbon price λ c (t) is used to characterize the carbon emission impact corresponding to electricity consumption behavior at different times and nodes. When a microgrid receives the carbon factor or carbon price signal, it can use it as low-carbon operation guidance information to adjust local photovoltaic consumption, energy storage charging and discharging, and electricity purchase and sale strategies. Similar to the price signal, the carbon signal does not directly serve as a physical constraint on the power grid, but rather indirectly changes the power exchange outcome by influencing the optimization decisions of the microgrid and distribution network.

[0223] Finally, state / capacity support variables are used to support multi-microgrid coordination at the distribution network layer. After completing local autonomous optimization, in addition to generating a distribution-microgrid switching power plan, the microgrid can also report its inter-microgrid switching demand P to the distribution network layer. req MG,i (t), Exchangeable power capacity P max MG,i (t), surplus photovoltaic power P sur PV,i (t) and available energy for energy storage E avaESS,i Information such as (t) is provided. These variables do not directly represent the final power exchange result, but rather characterize whether a microgrid has the capacity to supply power to other microgrids, whether it has external power purchase needs, and its ability to participate in energy sharing. Based on these state / capability support variables and combined with the regional network security verification results, the distribution network layer determines whether energy sharing between microgrids is feasible and further formulates the inter-microgrid exchange power P. MG,ij (t).

[0224] Therefore, the core of the coordinated variable operation support mechanism lies in the following: power variables need to be verified for safety, price variables are used for economic guidance, carbon variables are used for low-carbon guidance, and state / capacity support variables are used for judging the mutual assistance capability of multiple microgrids. These four types of variables jointly support the main-distribution-microgrid coordinated control architecture to move from "variable exchange" to "operation execution".

[0225] Embodiments of the present invention also provide a coordination variable communication connection mechanism, which ensures reliable transmission of coordination variables among the main network, distribution network, microgrid, and terminal devices. This is a crucial prerequisite for the implementation of the main-distribution-microgrid collaborative control architecture. Based on the established main-distribution-microgrid collaborative architecture, the communication system should revolve around the connection relationships between the main network dispatch center, distribution network dispatch center, microgrid edge nodes, and terminal devices.

[0226] The main transmission between the main grid dispatch center and the distribution grid dispatch center is the main distribution switching power P. GD (t), Distribution network side main and distribution switching power demand Preq GM(t), Purchase and sale price λ buy (t), λ sell (t), carbon price λ c (t) and coordination variables such as system-level low-carbon guidance information. This level of communication has high requirements for reliability and security, and should rely on the power dispatch data network for transmission, and adopt the IEC 60870-5-104 protocol to realize remote communication of dispatch data.

[0227] The main transmission of distribution network switching power P between the distribution network dispatch center and the microgrid edge node is the distribution-microgrid switching power. DM,i (t) Distribution micro-switching power plan P formed by microgrid autonomous optimization plan DM,i (t), node electrocarbon factor C EF,i (t), electricity purchase and sale prices, and state / capacity supporting variables related to microgrid inter-network collaboration. For microgrid inter-network collaboration scenarios, microgrid edge nodes need to upload information such as inter-grid exchange demand, exchangeable power capacity, surplus photovoltaic power, and available energy storage to the distribution network layer; the distribution network layer then forms the inter-grid exchange power P based on the above information. MG,ij(t), and distribute it to the relevant microgrid edge nodes. This layer needs to meet both scheduling and control requirements and support lightweight data access on the edge side. Therefore, the IEC 61850 standard can be used to achieve unified modeling and data interaction, and the MQTT protocol can be used to achieve publish / subscribe lightweight communication.

[0228] The microgrid edge nodes primarily handle status data acquisition and control execution with devices such as photovoltaic inverters, energy storage converters, and flexible load control terminals. This data level is characterized by a wide variety of device types, a large number of connected devices, and fine-grained communication. Device interconnection can be achieved using methods such as Modbus TCP / IP, MQTT, or IEC 61850. Modbus TCP / IP is suitable for data acquisition from industrial equipment such as photovoltaic inverters and energy storage devices, while MQTT is suitable for status updates and message pushes between edge nodes and numerous lightweight terminals.

[0229] For microgrid collaboration scenarios, direct, unmanaged point-to-point communication between microgrids is not advisable. Instead, it should be organized through the distribution network coordination layer. Each microgrid uploads information such as its exchangeable power capacity, surplus renewable energy output, available energy storage capacity, and inter-microgrid exchange needs to the distribution network layer. The distribution network layer then coordinates and formulates an inter-microgrid power exchange plan. This ensures that microgrid collaboration is managed under the security constraints of the distribution network and avoids operational risks arising from disorderly interactions between multiple microgrids.

[0230] To improve communication reliability, a primary / backup link or multi-path transmission mechanism should be established. For primary / secondary switching power, secondary / micro-switching power, inter-micronet switching power, price signals, carbon signals, and critical status / capability support variables, a combination of primary and backup communication links is recommended. When the primary link fails, the system can switch to the backup link to ensure the continued availability of critical coordination variables.

[0231] In summary, the master-distributor-micro-network collaborative control and communication mechanism can be summarized as follows: the master and distribution networks rely on the scheduling data network and IEC104 to achieve highly reliable scheduling communication; the distribution and micro-networks rely on IEC61850 and MQTT to achieve scheduling control and edge data interaction; within the micro-network, terminal access is achieved through protocols such as Modbus TCP / IP and MQTT; and the collaboration between micro-networks is organized through the distribution network layer, relying on the status / capability support variables uploaded by the micro-networks to achieve controlled mutual assistance and avoid disordered point-to-point interaction.

[0232] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A low-carbon optimization scheduling and control method for main grid-distribution network-microgrid coordinated operation based on coordination variable calculation, characterized in that: The scheduling and control steps include the following: Step S1: At the beginning of each scheduling cycle, the main network layer, distribution network layer, and microgrid layer respectively obtain the basic data required for coordinated scheduling, including: Main network side data: The main network layer obtains the electricity purchase price λ. buy (t), Electricity sales price λ sell (t), Main grid reference carbon factor C base (t), carbon price λ c (t), Maximum power limit of main distribution switching P max GD (t), Lower limit of main distribution switching power P min GD (t); Distribution network side data: The distribution network layer obtains the equivalent load P of the distribution network non-microgrid foundation. D,base (t), Distribution network loss power P loss,D (t), Maximum power P of each micro-interface max DM,i (t), lower power limit P of each micro-interface min DM,i (t), and the maximum allowable transmission power P of the inter-micronet mutual assistance channels. max line,ij (t); Microgrid-side data: The microgrid layer obtains the predicted load power P of the i-th microgrid. L,i (t), Photovoltaic Predicted Output P PV,i (t), State of Charge (SOC) i (t), Rated energy storage capacity E i Energy storage minimum state of charge (SOC) min i Energy storage maximum state of charge (SOC) max i Maximum charging power P of energy storage ch,max ESS,i (t), Maximum discharge power of energy storage P dis,max ESS,i (t); Step S2: The main grid layer or distribution grid layer calculates the nodal carbon factor (CEF) of each microgrid access node based on the electricity carbon emission flow theory. i (t), and the nodal electrocarbon factor CEF i (t), Main grid reference carbon factor C base (t) and carbon price λ c (t) is sent to the corresponding microgrid as a low-carbon signal; Step S3: The i-th microgrid edge control node calculates the available energy of energy storage based on the local energy storage state of charge and energy storage capacity; the i-th microgrid calculates the surplus photovoltaic power based on the predicted photovoltaic output, local load, and energy storage rechargeable power. Step S4: The i-th microgrid calculates the autonomously optimized distribution micro-switching power plan based on the local load, photovoltaic, energy storage, and flexible load operating status; Step S5: The i-th microgrid calculates the inter-microgrid coordination requirements based on local load, photovoltaic output, and energy storage discharge capacity, and further calculates the microgrid exchange capacity; Step S6: After receiving the distribution network switching power plan reported by each microgrid, the distribution network layer calculates the main distribution switching power demand on the distribution network side by combining the distribution network basic load and distribution network loss. Step S7: After receiving the main distribution switching power demand reported by the distribution network layer, the main network layer calculates the main distribution switching power plan based on the main distribution tie line capacity constraints. Step S8: The distribution network layer calculates the main distribution power deviation based on the main distribution switching power plan issued by the main network layer, and allocates the main distribution power deviation according to the adjustable capability of each microgrid to obtain the distribution-micro switching power boundary of the i-th microgrid. Step S9: The distribution network layer calculates the inter-micronetwork switching power plan in a unified manner based on the inter-micronetwork coordination requirements and switching capabilities reported by each micronetwork. Step S10: After the distribution network layer forms the distribution micro-grid switching power and the microgrid inter-grid switching power, it performs a safety check on the distribution network operation status and issues control boundaries, including node voltage check and line capacity check. Step S11: The i-th microgrid adjusts its local energy storage charging and discharging, flexible load, and photovoltaic consumption strategies to ensure that the actual distribution microgrid switching power tracks the distribution microgrid switching power boundary issued by the distribution grid layer and feeds back the actual power. Step S12: The distribution network layer summarizes the execution deviations of each microgrid, calculates the total deviation for the region, and performs rolling feedback correction.

2. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 1, characterized in that: The specific method for step S2 is as follows: The nodal electrocarbon factor is calculated based on the nodal carbon flux balance relationship, and the calculation formula is as follows: ； Among them, CEF i (t) represents the node carbon factor of the i-th microgrid access node at time t; P out i (t) represents the outflow power or equivalent supply power of node i at time t; Ω in i Represents the set of upstream nodes that inject power into node i; CEF k (t) represents the nodal carbon factor of upstream node k at time t; P ki (t) represents the active power transmitted from node k to node i; G i Represents the set of local power sources for access node i; η g P represents the carbon emission coefficient per unit of electricity generated by the g-th local power source; g,i (t) represents the active power output of the g-th local power source at node i; when node i has no local power source. Take zero.

3. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 2, characterized in that: The specific method for step S3 is as follows: The i-th microgrid edge control node calculates the available energy E of the energy storage based on the local energy storage state of charge and energy storage capacity. ava ESS,i (t), the calculation formula is: ； Among them, E ava ESS,i (t) represents the energy that the i-th microgrid energy storage can still release after satisfying the minimum state of charge constraint at time t; SOC i (t) represents the state of charge (SOC) of the i-th microgrid energy storage at time t; min i E represents the minimum allowable state of charge for the i-th microgrid energy storage; i This represents the rated energy storage capacity of the i-th microgrid; The i-th microgrid further calculates the energy storage charging power used for photovoltaic power consumption, using the following formula: ； Among them, P ava,ch ESS,i (t) represents the charging power that the i-th microgrid energy storage can absorb from photovoltaics at time t; P ch,max ESS,i Represents the maximum charging power of the i-th microgrid energy storage; SOC max i The maximum state of charge allowed for the i-th microgrid energy storage is represented by Δt; Δt represents the time interval between two adjacent scheduling moments. The i-th microgrid calculates its surplus photovoltaic power based on the predicted photovoltaic output, local load, and rechargeable energy storage power. The calculation formula is as follows: ； Among them, P sur PV,i (t) represents the surplus photovoltaic power of the i-th microgrid at time t; P PV,i (t) represents the predicted photovoltaic output of the i-th microgrid at time t; P L,i (t) represents the predicted load power of the i-th microgrid at time t.

4. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 3, characterized in that: The specific method for step S4 is as follows: The i-th microgrid calculates the autonomous optimization-based distribution-microgrid switching power plan P based on the operating status of local load, photovoltaic, energy storage, and flexible load. plan DM,i (t), the calculation formula is: ； Among them, P plan DM,i (t) represents the distribution-micro-switching power plan formed by the i-th microgrid autonomous optimization; P ch ESS,i (t) represents the charging power of the i-th microgrid energy storage at time t; P dis ESS,i (t) represents the discharge power of the i-th microgrid energy storage at time t; P inc FL,i (t) represents the increase in power of the i-th microgrid flexible load at time t; P dec FL,i (t) represents the power reduction of the i-th microgrid flexible load at time t; When P plan DM,i When (t)>0, it means that the i-th microgrid plans to purchase electricity from the distribution network; When P plan DM,i When (t) < 0, it means that the i-th microgrid plans to send power to the distribution network.

5. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 4, characterized in that: The specific method for step S5 is as follows: The i-th microgrid calculates the inter-microgrid coordination demand P based on local load, photovoltaic output, and energy storage discharge capacity. req MG,i (t): First, calculate the discharge power of the stored energy. The calculation formula is as follows: ； Among them, P ava,dis ESS,i (t) represents the power of the i-th microgrid energy storage available for discharge support at time t; P dis,max ESS,i (t) represents the maximum discharge power of the i-th microgrid energy storage; Then, the inter-microgrid collaboration requirements are calculated using the following formula: ； Among them, P req MG,i (t) represents the power demand that the i-th microgrid needs to be supported by other microgrids when the local photovoltaic and energy storage discharge capacity is insufficient to meet the load. Further calculations of the microgrid's switchable capacity are performed using the following formula: ； Among them, P max MG,i (t) represents the maximum mutual power that the i-th microgrid can provide to other microgrids at time t.

6. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 5, characterized in that: The specific method for step S6 is as follows: Calculate the main distribution switching power demand P on the distribution network side. req GM,i (t), the calculation formula is: ； Among them, P req GM (t) represents the main distribution switching power demand reported by the distribution network layer to the main network layer; P D,base (t) represents the basic equivalent load power within the distribution network area excluding microgrids; N represents the number of microgrids; P loss,D (t) represents the power loss of the distribution network, which is specifically obtained through distribution network power flow calculation. The calculation formula is as follows: ； Among them, L D Represents the set of distribution network lines; r1 represents the resistance of the l-th distribution line; I l (t) represents the current of the l-th distribution line at time t.

7. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 6, characterized in that: The specific method for step S7 is as follows: The main network layer receives the P reported by the distribution network layer. req GM After (t), calculate the planned main and distribution switching power P based on the main and distribution tie line capacity constraints. GD (t), the calculation formula is: ； Among them, P GD (t) represents the main distribution switching power plan issued from the main network layer to the distribution network layer; P max GD (t) represents the upper limit of the main distribution switching power; P min GD (t) represents the lower limit of the main distribution network's switching power; when the distribution network is allowed to feed back power to the main network, P max GD (t) takes a negative value.

8. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 7, characterized in that: The specific method for step S8 is as follows: The distribution network layer uses the P issued by the main network layer. GD (t), calculate the main distribution power deviation, the calculation formula is: ； Where, ∆P D (t) represents the deviation between the main power switching plan issued by the main grid and the original power demand on the distribution network side; The distribution network layer adjusts ∆P based on the adjustability of each microgrid. D (t) is used for allocation to obtain the distribution-micro-switching power boundary of the i-th microgrid. The calculation formula is as follows: ； Among them, P DM,i (t) represents the distribution-micro-switching power boundary sent from the distribution network layer to the i-th microgrid; α i (t) represents the allocation coefficient for the main distribution power deviation correction undertaken by the i-th microgrid, and the calculation formula is: ； Among them, A i (t) represents the adjustability of the i-th microgrid at time t; A k (t) represents the adjustability of the k-th microgrid at time t; The adjustability A of the i-th microgrid i The formula for calculating (t) is: ； Among them, P inc,max FL,i P represents the maximum increase in power that the i-th microgrid flexible load can achieve; dec,max FL,i This indicates the maximum power reduction that can be achieved by the flexible load of the i-th microgrid. The power boundary of the microswitch is satisfied as follows: ； Among them, P min DM,i (t) represents the lower limit of the power of the i-th microgrid distribution microswitch; P max DM,i (t) represents the upper limit of the power of the i-th microgrid distribution microswitch.

9. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 8, characterized in that: The specific method for step S9 is as follows: The distribution network layer bases its work on the inter-micronetwork coordination requirements reported by each micronetwork. req MG,i (t) and exchangeability P max MG,i (t), unified calculation of inter-microgrid switching power plan: When the i-th microgrid has exchangeable capacity and the j-th microgrid has coordination needs, the distribution network layer calculates the planned exchange power from microgrid i to microgrid j using the following formula: ； Among them, P MG,ij (t) represents the power exchange plan between microgrid i and microgrid j; P max MG,i (t) represents the maximum mutual support power that microgrid i can provide to other microgrids; P req MG,j (t) represents the power requirement of microgrid j that it needs to support from other microgrids; P max line,ij (t) represents the maximum allowable transmission power when power mutual assistance is achieved between microgrid i and microgrid j through the distribution network channel; The switching power between microgrids satisfies an antisymmetric relationship: ； Among them, P MG,ij (t)>0 indicates that microgrid i supplies power to microgrid j, P MG,ij (t) < 0 indicates that microgrid j supplies power to microgrid i.

10. The method for coordinated low-carbon optimization scheduling and control of the main grid-distribution network-microgrid based on coordination variable calculation according to claim 9, characterized in that: The specific method for step S10 is as follows: In the formation of P DM,i (t) and P MG,ij After (t), a safety check is performed on the distribution network operation status, including node voltage check and line capacity check, which respectively meet the constraints: ； ； Among them, V n (t) represents the voltage of distribution network node n at time t; V min n and V max n S represents the lower and upper voltage limits of node n, respectively; l (t) represents the apparent power of the l-th distribution line at time t; S max l This indicates the maximum permissible apparent power of the l-th distribution line; If the security check meets the constraints, the distribution network layer sends P to each microgrid. DM,i (t), P MG,ij (t), λ buy (t), λ sell (t), CEF i (t) and λ c (t); If the security check does not meet the constraints, the distribution network layer returns to steps S8 and S9 to readjust the distribution micro-switching power boundary and the inter-micro-network switching power plan.

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