Flexible resource control method and device considering differentiated characteristics of multiple balance areas

Abstract

The present invention relates to the field of distribution network flexibility resource management and dispatch optimization technology, and in particular to a flexibility resource control method and device that takes into account the differentiated characteristics of multiple balancing areas, wherein the method includes: obtaining long-term and short-term parameter data of the distribution network system and flexibility resources, and inputting them into a pre-established flexibility resource mathematical model and a mathematical model of different types of balancing areas, respectively, to calculate long-term and short-term characteristic evaluation indicators; formulating an installed capacity plan based on the long-term characteristic evaluation indicators; excluding the balancing area operation mode that cannot be operated based on the special items of the short-term evaluation indicators, and then formulating an optimized dispatching plan based on the installed capacity plan, and determining whether the plan meets the safety operation requirements. If so, the optimized dispatching plan is output as the final dispatching plan, otherwise it is readjusted. Thus, the traditional resource dispatching method only considers a single balancing area operation mode, resulting in substandard economic benefits, inability to guarantee operation safety, and reduced new energy consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network flexibility resource management and dispatch optimization, and in particular to a flexibility resource control method and device taking into account differentiated characteristics of multiple balancing areas. Background Art

[0002] Distributed energy, energy storage devices, adjustable loads and other flexible resources are aggregated and operated through different forms of balancing areas such as microgrids, virtual power plants, and integrated source-grid-load-storage, which have gradually become an important means to promote the consumption of distributed power sources and ensure power supply. Therefore, distinguishing the advantages and disadvantages of different types of balancing area technologies, comprehensively considering and comparing the operating effects of different balancing area operation modes, and then designing a reasonable distribution network-balancing area collaborative flexibility resource scheduling planning method to achieve optimal scheduling of flexible resources in the distribution network is one of the inevitable key issues in the construction and development of new power systems and balancing areas in the future.

[0003] A microgrid is a small, localized power network system with a certain degree of autonomy, usually composed of a variety of distributed power sources, energy storage devices, and loads. When flexible resources are operated in the form of a microgrid, due to the conversion between the microgrid networking mode and the island operation mode, its internal power needs to be balanced at all times, and it is limited by the scale effect. The microgrid cannot fully exert the scale effect, resulting in a higher unit cost of operation.

[0004] Virtual power plant is an emerging power system operation mode. Its core concept can be summarized as "communication" and "aggregation". It integrates and optimizes a variety of distributed resources (such as wind energy, photovoltaic energy, natural gas energy, etc.) to achieve flexible control of the power system and coordinated optimization of resources. Virtual power plants are guided by economic benefits and pursue the maximization of their own interests, but ignore the topological influence of the distribution network. In practice, excessive wind and solar power or load output, unstable and unreliable network topology, etc. may cause voltage limit violations and network congestion in the distribution network under virtual power plant dispatching.

[0005] "Source, grid, load and storage integration" refers to the organic integration of energy (such as photovoltaic, wind power, etc.), power grid, power load and energy storage system to achieve efficient use of energy and optimize the balance between energy supply and demand to form a comprehensive energy system. The characteristics of the source, grid, load and storage integrated balancing area are that the main components of the current power system are centrally dispatched and managed, and the influence and constraints of the distribution network's own architecture are emphasized. In terms of the safe and stable operation of the system, it can make up for the deficiencies of virtual power plants and other operating modes to a certain extent. However, due to the constraints and losses of the distribution network itself, the effective output of the system is limited, and there are deficiencies in economy.

[0006] The scheduling optimization of flexibility resources achieved through different types of balancing area modes has different characteristics and advantages, but also has corresponding deficiencies and shortcomings. Faced with the increasingly diverse forms and increasing numbers of distribution network flexibility resources, there is an urgent need for a resource regulation method that considers the differences in multiple balancing area modes and model characteristics, flexibly uses multi-dimensional feature evaluation indicators to make decisions, and judges and selects the operating mode of distribution network flexibility resources, so as to formulate a reasonable, safe, stable, and expected flexibility resource scheduling plan. Summary of the invention

[0007] The present invention provides a flexible resource control method and device that takes into account the differentiated characteristics of multiple balance zones, so as to solve the problems that the traditional resource scheduling method only considers a single balance zone operation mode, resulting in economic benefits not meeting the standards after system operation, the inability to ensure operational safety, and reduced new energy consumption.

[0008] The first aspect of the present invention provides a flexibility resource control method that takes into account the differentiated characteristics of multiple balancing areas, including the following steps: respectively establishing a first mathematical model of a target flexibility resource and a second mathematical model of different types of balancing areas; obtaining long-term parameter data of a target distribution network system and the target flexibility resource, and inputting the long-term parameter data into the first mathematical model and the second mathematical model to calculate long-term characteristic evaluation indicators; formulating an installed capacity plan for the target flexibility resource based on the long-term characteristic evaluation indicators; obtaining short-term parameter data of the target distribution network system and the target flexibility resource, and inputting the short-term parameter data into the first mathematical model and the second mathematical model to calculate short-term characteristic evaluation indicators; using special items of the short-term characteristic evaluation indicators as feasibility criteria for the balancing area operation mode. , to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and obtain multiple actual balancing area operation modes, wherein the balancing area operation modes include virtual power plant operation modes, microgrid operation modes and source-grid-load-storage integrated operation modes; based on the installed capacity planning, obtain the scheduling plans and operation results under the multiple actual balancing area operation modes to formulate an optimized scheduling plan for the target flexibility resources; input the optimized scheduling plan for the target flexibility resources into the target distribution network system to determine whether the optimized scheduling plan for the target flexibility resources meets the preset distribution network safety operation requirements. If so, the optimized scheduling plan for the target flexibility resources is output as the final scheduling plan. Otherwise, a new optimized scheduling plan for the target flexibility resources is re-formulated until the preset distribution network safety operation requirements are met.

[0009] Optionally, the short-term characteristic evaluation index includes at least one of a reliability index, a stability index, a flexibility index, an economic index and a coordination index, wherein the reliability index includes the power exchange rate between the distributed power source and the main grid, the power supply utilization rate of the distributed power source and the power supply reliability rate; the stability index includes the power load adaptability, the proportion of adjustable power sources, the power balance degree and the system inertia energy supply proportion; the flexibility index includes the adjustable power range and the climbing rate; the economic index includes the power grid loss rate and the demand response shortage power proportion; the coordination index includes the self-generated and self-used power shortage proportion, the self-generated and self-used power surplus proportion and the energy storage power absorption capacity; the special items of the short-term characteristic evaluation index include the power exchange rate between the distributed power source and the main grid, the power load adaptability and the power grid loss rate.

[0010] Optionally, the special items of the short-term characteristic evaluation index are used as feasibility criteria for the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and multiple actual balancing area operation modes are obtained, including:

[0011] According to the distributed power source and the main grid power exchange rate in the reliability index, it is preliminarily determined whether the target flexibility resource is suitable for operation in the virtual power plant operation mode. If the distributed power source and the main grid power exchange rate is greater than 0, the target flexibility power generation resource meets the load demand of the target distribution network system, and there is surplus electricity to trade with the grid to obtain income, which meets the basic conditions for the virtual power plant to participate in electricity market transactions to obtain income and can be operated in the virtual power plant operation mode. Otherwise, the virtual power plant operation mode is excluded to obtain the first exclusion result; according to the power load adaptability of the stability index, it is preliminarily determined whether the target flexibility resource is suitable for operation in the microgrid operation mode. If the power load adaptability is greater than 1, it meets the internal power balance constraint of the microgrid and can If the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode, the target flexibility resource can be operated in the microgrid operation mode; otherwise, the microgrid operation mode is excluded to obtain a second exclusion result; based on the grid loss rate of the economic indicator, it is preliminarily determined whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode; if the grid loss rate is higher than 10%, it means that the economy of the target flexibility resource cannot be guaranteed after considering the distribution network constraints under the source-grid-load-storage integrated operation mode, then the source-grid-load-storage integrated operation mode is excluded; otherwise, the economy of the source-grid-load-storage integrated operation mode can be basically guaranteed and the target flexibility resource can be operated in the source-grid-load-storage integrated operation mode to obtain a third exclusion result; the multiple actual balancing area operation modes are determined based on the first exclusion result, the second exclusion result and the third exclusion result.

[0012] Optionally, the optimized scheduling scheme of the target flexibility resource is input into the target distribution network system to determine whether the optimized scheduling scheme of the target flexibility resource meets the preset distribution network safety operation requirements. If so, the optimized scheduling scheme of the target flexibility resource is output as the final scheduling scheme. Otherwise, a new optimized scheduling scheme of the target flexibility resource is re-formulated until the preset distribution network safety operation requirements are met, including:

[0013] The optimal scheduling scheme of the target flexibility resource is input into the target distribution network system to obtain the voltage of each node and the power flow on the branch; it is judged whether the voltage of each node exceeds the first preset upper limit or is lower than the second preset lower limit, and whether the power flow on the branch exceeds the third preset upper limit; if the voltage of each node exceeds the first preset upper limit and the power flow on the branch exceeds the third preset upper limit, or if the voltage of each node is lower than the second preset upper limit and the power flow on the branch exceeds the third preset upper limit, then the optimal scheduling scheme of the target flexibility resource meets the preset safe operation requirements of the distribution network, and the optimal scheduling scheme of the target flexibility resource is output as the final scheduling scheme; otherwise, according to the scheduling schemes and operating effects under the multiple actual balancing area operation modes, a new optimal scheduling scheme for the flexibility resource is re-formulated and input into the target distribution network system to judge whether the new optimal scheduling scheme for the target flexibility resource meets the preset safe operation requirements of the distribution network, and the formulation and judgment process is iteratively executed until the preset safe operation requirements of the distribution network are met.

[0014] The second aspect of the present invention provides a flexibility resource control device that takes into account the differentiated characteristics of multiple balancing zones, including: an establishment module, used to respectively establish a first mathematical model of a target flexibility resource and mathematical models of different types of balancing zones; a first calculation module, used to obtain long-term parameter data of a target distribution network system and the target flexibility resource, and input the long-term parameter data into the first mathematical model and the second mathematical model to calculate long-term characteristic evaluation indicators under long-term parameters; a first formulation module, used to formulate an installed capacity plan for the target flexibility resource based on the long-term characteristic evaluation indicators; a second calculation module, used to obtain short-term parameter data of the target distribution network system and the target flexibility resource, and input the short-term parameter data into the first mathematical model and the second mathematical model to calculate short-term characteristic evaluation indicators; an exclusion module, used to use special items of the short-term characteristic evaluation indicators as The feasibility criteria of the balancing area operation mode are used to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and obtain multiple actual balancing area operation modes, wherein the balancing area operation modes include virtual power plant operation mode, microgrid operation mode and source-grid-load-storage integrated operation mode; the second formulation module is used to obtain the scheduling plans and operation results under the multiple actual balancing area operation modes based on the installed capacity planning, so as to formulate the optimized scheduling plan for the target flexibility resources; the judgment module is used to input the optimized scheduling plan for the target flexibility resources into the target distribution network system to determine whether the optimized scheduling plan for the target flexibility resources meets the preset distribution network safety operation requirements. If so, the optimized scheduling plan for the target flexibility resources is output as the final scheduling plan. Otherwise, a new optimized scheduling plan for the target flexibility resources is re-formulated until the preset distribution network safety operation requirements are met.

[0015] Optionally, the short-term characteristic evaluation index includes at least one of a reliability index, a stability index, a flexibility index, an economic index and a coordination index, wherein the reliability index includes the power exchange rate between the distributed power source and the main grid, the power supply utilization rate of the distributed power source and the power supply reliability rate; the stability index includes the power load adaptability, the proportion of adjustable power sources, the power balance degree and the system inertia energy supply proportion; the flexibility index includes the adjustable power range and the climbing rate; the economic index includes the power grid loss rate and the demand response shortage power proportion; the coordination index includes the self-generated and self-used power shortage proportion, the self-generated and self-used power surplus proportion and the energy storage power absorption capacity; the special items of the short-term characteristic evaluation index include the power exchange rate between the distributed power source and the main grid, the power load adaptability and the power grid loss rate.

[0016] Optionally, the exclusion module includes: a first exclusion unit, used to preliminarily determine whether the target flexibility resource is suitable for operation in the virtual power plant operation mode according to the power exchange rate between the distributed power source and the main grid in the reliability index; if the power exchange rate between the distributed power source and the main grid is greater than 0, the target flexibility power generation resource meets the load demand of the target distribution network system, and has surplus electricity to trade with the grid to obtain income, which meets the basic conditions for the virtual power plant to participate in electricity market transactions to obtain income and can operate in the virtual power plant operation mode; otherwise, the operation mode of the virtual power plant is excluded to obtain the first exclusion result; a second exclusion unit, used to preliminarily determine whether the target flexibility resource is suitable for operation in the microgrid operation mode according to the power load adaptability of the stability index; if the power load adaptability is greater than 1, it meets the internal power of the microgrid. rate balance constraint, and can operate in the microgrid operation mode; otherwise, the microgrid operation mode is excluded to obtain a second exclusion result; a third exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode according to the grid loss rate of the economic indicator; if the grid loss rate is higher than 10%, it means that the economy of the target flexibility resource cannot be guaranteed after considering the distribution network constraint under the source-grid-load-storage integrated operation mode, then the source-grid-load-storage integrated operation mode is excluded; otherwise, the economy of the source-grid-load-storage integrated operation mode can be basically guaranteed, and it can operate in the source-grid-load-storage integrated operation mode to obtain a third exclusion result; a determination unit is used to determine the multiple actual balancing area operation modes according to the first exclusion result, the second exclusion result and the third exclusion result.

[0017] Optionally, the judgment module includes: an acquisition unit, used to input the optimal scheduling plan of the target flexibility resource into the target distribution network system to obtain the voltage of each node and the power flow on the branch; a judgment unit, used to judge whether the voltage of each node exceeds a first preset upper limit or is lower than a second preset lower limit, and whether the power flow on the branch exceeds a third preset upper limit. If the voltage of each node exceeds the first preset upper limit and the power flow on the branch exceeds the third preset upper limit or if the voltage of each node is lower than the second preset upper limit and the power flow on the branch exceeds the third preset upper limit, then the optimal scheduling plan of the target flexibility resource meets the preset distribution network safety operation requirements, and the optimal scheduling plan of the target flexibility resource is output as the final scheduling plan. Otherwise, according to the scheduling plans and operating results under the multiple actual balancing area operation modes, a new optimal scheduling plan for the flexibility resource is re-formulated and input into the target distribution network system to judge whether the new optimal scheduling plan for the target flexibility resource meets the preset distribution network safety operation requirements, and iteratively execute the formulation and judgment process until the preset distribution network safety operation requirements are met.

[0018] An embodiment of the third aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a flexible resource control method that considers differentiated characteristics of multiple balance zones as described in the above embodiments.

[0019] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned flexibility resource regulation method considering differentiated characteristics of multiple balance zones.

[0020] The embodiments of the present invention propose a flexibility resource control method and device that take into account the differentiated characteristics of multiple balancing areas. By considering the differences and model characteristics of the three main balancing area modes of microgrid, virtual power plant and source-grid-load-storage integration, the flexibility resources in the distribution network system are optimized and scheduled. The balancing area characteristic evaluation indicators are used to screen out different balancing area control modes and formulate reasonable scheduling plans to effectively avoid unreasonable allocation of resources and system risks, maintain the stability and security of the distribution network, and output scheduling plans and operating effects under different balancing area operation modes, so as to provide decision makers with comprehensive data support and achieve the purpose of scientific decision-making and optimization of operation strategies.

[0021] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A flow chart of a flexible resource control method considering differentiated characteristics of multiple balance zones provided by an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of a specific implementation of a flexible resource control method considering differentiated characteristics of multiple balance zones provided by an embodiment of the present invention;

[0025] Figure 3 A 33-node network connection diagram provided by an embodiment of the present invention;

[0026] Figure 4 A diagram of transaction electricity price and load conditions provided by an embodiment of the present invention;

[0027] Figure 5 A wind and solar power forecast output diagram provided by an embodiment of the present invention;

[0028] Figure 6 A diagram showing the output of each power source under the microgrid dispatching scheme provided in an embodiment of the present invention;

[0029] Figure 7 An interactive power curve diagram between the system, energy storage and power grid under the microgrid dispatching condition provided by an embodiment of the present invention;

[0030] Figure 8 A comparison chart of wind and solar power prediction and actual output under microgrid dispatching provided by an embodiment of the present invention;

[0031] Fig. 9 A diagram showing the charging and discharging status of an energy storage system under microgrid dispatching provided by an embodiment of the present invention;

[0032] Fig.10 A diagram showing the output of each power source under the virtual power plant scheduling provided by an embodiment of the present invention;

[0033] Fig.11 A graph showing the relationship between total output and transaction price changes in the case of virtual power plant scheduling provided by an embodiment of the present invention;

[0034] Fig.12 An interactive power curve diagram between the system, energy storage and power grid under the virtual power plant dispatching provided by an embodiment of the present invention;

[0035] Fig.13 A comparison chart of wind and solar power forecast and actual output in the case of virtual power plant dispatch provided by an embodiment of the present invention;

[0036] Fig.14 A diagram showing the charging and discharging status of an energy storage system under virtual power plant scheduling provided by an embodiment of the present invention;

[0037] Fig.15 A diagram showing the output of each power source in the case of source-grid-load-storage integrated scheduling provided by an embodiment of the present invention;

[0038] Fig.16 An interactive power curve diagram between the system, energy storage and power grid under the source-grid-load-storage integrated scheduling provided by an embodiment of the present invention;

[0039] Fig.17 A comparison chart of wind and solar power prediction and actual output in the case of source-grid-load-storage integrated scheduling provided by an embodiment of the present invention;

[0040] Fig.18 A diagram of the charging and discharging status of the energy storage system under the source-grid-load-storage integrated scheduling provided by an embodiment of the present invention;

[0041] Fig.19 A distribution network voltage distribution diagram for different time periods under the microgrid scheduling provided by an embodiment of the present invention;

[0042] Fig. 20 A distribution network voltage distribution diagram for different time periods under the virtual power plant scheduling provided by an embodiment of the present invention;

[0043] Fig.21 The voltage distribution diagram of the distribution network in different time periods under the source-grid-load-storage integrated scheduling provided by the embodiment of the present invention;

[0044] Fig. 22 A power flow comparison diagram of line 1-2 under different scheduling conditions provided by an embodiment of the present invention;

[0045] Fig.23 A block diagram of a flexible resource control device considering differentiated characteristics of multiple balancing areas provided by an embodiment of the present invention;

[0046] Fig.24 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0048] The following describes a method and apparatus for flexible resource control that takes into account differentiated characteristics of multiple balancing areas according to an embodiment of the present invention with reference to the accompanying drawings.

[0049] Figure 1 A flow chart of a flexible resource control method considering differentiated characteristics of multiple balance zones provided in an embodiment of the present invention.

[0050] like Figure 1 As shown, the flexibility resource regulation method considering the differentiated characteristics of the multi-balance zone includes the following steps:

[0051] In step S101, a first mathematical model of a target flexibility resource and second mathematical models of different types of balancing areas are established respectively.

[0052] In some embodiments, the first mathematical model includes the operating costs of wind turbines, photovoltaic generators, diesel generators and energy storage systems, and the second mathematical model includes the optimization model of the microgrid operation mode and its constraints, the optimization model of the virtual power plant operation mode and its constraints, and the optimization model of the source-grid-load-storage integrated operation mode and its constraints.

[0053] In the actual implementation process, the first mathematical model of the target flexibility resource established in the embodiment of the present invention refers to the operation cost function of the target flexibility resource, which is as follows:

[0054] (1) Wind turbine operating costs:

[0055] C WT =C B,WT +C O,WT (1)

[0056] in,

[0057]

[0058]

[0059] In the formula, C B,WT , C O,WT They are the annual investment and construction cost and annual operation and maintenance cost of the wind turbine, is the rated power of each wind turbine, γ is the discount rate, TL is the planning period of the balancing area, c B,WT 、c O,WT are the power cost coefficient and operation and maintenance cost coefficient of the wind turbine respectively;

[0060] (2) Operation cost of photovoltaic generator set:

[0061] C PV =C B,PV +C O,PV (4)

[0062] in,

[0063]

[0064]

[0065] In the formula, C B,PV , C O,PV They are the annual investment cost and annual operation and maintenance cost of photovoltaic cells, is the rated power of each fan, c B,PV 、c O,PV are the power cost coefficient and operation and maintenance cost coefficient of photovoltaic cells respectively;

[0066] (3) Operating costs of conventional diesel generator sets:

[0067] C DE =C B,DE +C O,DE +C F,DE +C EG,DE (7)

[0068] in,

[0069]

[0070]

[0071]

[0072]

[0073] In the formula, C B,DE , C O,DE , C F,DE , C EG,DE They are the annual investment and construction cost of diesel engines, annual operation and maintenance cost, fuel combustion cost and environmental pollution treatment cost. P DE (t) are the rated power and actual output power of the diesel generator, c B,DE 、c O,DE 、c O,E are the purchase cost coefficient, fixed operation and maintenance cost coefficient and variable operation and maintenance cost coefficient of diesel generators, N is the number of diesel generators, T is the day-ahead scheduling period, a i , b i 、c i is the fuel consumption cost coefficient of diesel generators, m is the number of pollutants, mainly NO X 、SO 2 , CO 2 and CO;v m ,ω m They are respectively the environmental governance cost per unit emission of pollutant m and the emission of pollutant m per unit power output.

[0074] (4) Energy storage system operating costs:

[0075] C BES =C B,BES +C O,BES (12)

[0076] in,

[0077]

[0078]

[0079] In the formula, C B,BES , C O,BES They are the annual investment cost and operation and maintenance cost of the energy storage system, is the equivalent output power of the battery, is the rated capacity of the battery, c BP,B 、c BE,B 、c O,BESare the power cost coefficient, electricity cost coefficient and operation and maintenance cost coefficient of the energy storage system respectively, BY The table shows the planned service life of the battery.

[0080] Furthermore, the second mathematical model of different types of balancing areas established in the embodiment of the present invention refers to the objective functions and corresponding constraints of the three balancing area operation modes of microgrid, virtual power plant, and source-grid-load-storage integration, which are as follows:

[0081] (1) Optimization model of microgrid operation mode

[0082] Its objective function is as follows:

[0083] minF(t)=min[F 1 (t)+F 2 (t)+F 3 (t)](15)

[0084] in,

[0085]

[0086]

[0087]

[0088]

[0089] In the formula, F 1 (t), F 2 (t), F 3 (t) are the fuel combustion cost of each unit, the operation and management cost of each unit and the energy storage system, and the electricity transaction cost between the microgrid system and the large power grid. T is the day-ahead dispatch period. Y(P i,t ) is the combustion cost function of micro-source i, which is related to the model of each micro-source, N is the type of unit in the microgrid, C i,m is the operation management coefficient of unit t, C ES,t is the operation and management cost coefficient of the energy storage system, P i,t and P ES,t is the output power of unit i and the charging and discharging power of the energy storage system at time t, C grid,t is the cost of purchasing electricity from the grid at time t, P sell,t , P buy,t are the power sold and purchased by the microgrid and the large grid at time t, respectively, grid,t is the transaction electricity price between the microgrid and the large grid at time t.

[0090] The constraints are as follows:

[0091] Formula (20) is the power balance constraint within the microgrid, formula (21) is the power tie line constraint, formula (22) is the upper and lower limit constraints of each unit output, and formulas (23), (24), (25), and (26) are the capacity constraints, upper and lower limit constraints of the state of charge, charge and discharge constraints, and the state of charge equal constraint of the energy storage system, respectively.

[0092]

[0093]

[0094] P imin ≤P i (t)≤P imax (twenty two)

[0095] S min ≤ESS out,t ≤S max (twenty three)

[0096] SOC min ≤SOC≤SOC max (twenty four)

[0097] SOC t =λ·SOC t-1 +η·P cha,t -P dis,t (25)

[0098] SOC start =SOC end (26)

[0099] Where P i,t is the output of unit i at time t, P grid,t is the power exchange value between the microgrid and the large grid at time t, P ES,t is the energy storage output at time t. When it is positive, it is energy storage discharge, and when it is negative, it is energy storage charging. load,t For the power load, are the upper and lower limits of the power exchange value between the microgrid and the large grid, P imax , P imin is the upper and lower limits of the output of micro-source t, ESS out,t To store energy at time t, S max , S min is the upper and lower limits of energy storage capacity, SOC t is the state of charge value of the energy storage system at time t, SOC t-1 is the state of charge value of the energy storage system at time t-1, SOC max , SOC min is the upper and lower limits of the energy storage system’s state of charge, P cha,t , P dis,tare the charging and discharging power of the energy storage system at time t, λ and η are the charging and discharging efficiency and storage efficiency of the energy storage system, respectively. start , SOC end Respectively represent the initial and final states of the energy storage system;

[0100] (2) Optimization model of virtual power plant operation mode

[0101] Its objective function is as follows:

[0102]

[0103] in,

[0104]

[0105]

[0106] In the formula, is the total income of VPP, is the revenue of VPP from electricity purchase and sale in time period t, is the cost increment function of the ith controllable unit at time t in the VPP, is the total active power output of the ith controllable unit of VPP at time t, N Con is the total number of controllable units of VPP, is the controllable cost of the ith controllable unit of the VPP at time t, which mainly includes the fuel cost of conventional units and the operation and maintenance costs of photovoltaic, wind power and other units. is the operating cost of the i-th energy storage system ESS of VPP at time t, M t is the transaction price of electricity in the power market at time t, S out,t is the total output of the controllable units and energy storage system in the VPP at time t, S Load,t is the total load at time t;

[0107] The fuel costs of the VPP’s conventional units and the operation and maintenance costs of the photovoltaic, wind power, and energy storage systems are the same as those in the model established for the microgrid.

[0108] The constraints are as follows:

[0109] Formula (30) is the power balance constraint of the virtual power plant, formula (31) is the power market transaction constraint, and formula (32) is the system reserved reserve capacity constraint.

[0110]

[0111] 0≤S t ≤S max (31)

[0112]

[0113] In the formula, is the active power output of the ith controllable unit in the VPP, is the energy storage system discharge power, discharge power, p buy,t 、p sell,t is the power purchased and sold by VPP, P Load,t is the power load in the VPP, S t is the transaction volume between VPP and the power market at time t, S max is the upper limit of the amount of electricity traded between VPP and the electricity market, S i (t) is the start-stop coefficient of conventional unit i. When the coefficient is 0, it indicates the shutdown state, and when the coefficient is 1, it indicates the start state. d is the confidence factor of the renewable energy generator, N, N dpe are the number of conventional units and the number of renewable energy units, is the maximum output of the renewable energy unit, is the output of conventional unit i at time t, are the maximum and minimum outputs of conventional unit i respectively.

[0114] The upper and lower output constraints of each unit and the battery constraints are consistent with the constraints of the microgrid model.

[0115] (3) Optimization model of the integrated operation mode of power generation, grid, load and storage

[0116] Its objective function is as follows:

[0117] minF=C on +C F +C DR (33)

[0118] in,

[0119]

[0120]

[0121] C DR =M t ·S t (36)

[0122] In the formula, C on , C F , C DR are the operation and maintenance costs of each unit, the fuel cost of conventional units and the power grid purchase cost, respectively. The calculation formulas are as follows: (34)-(36), γ i is the unit operation and maintenance cost coefficient, P i (t) is the unit output active power, Y(Pi (t)) is the combustion cost function of power source i, which is related to the model of each micro source, M t is the transaction price, S t For trading electricity.

[0123] The constraints are as follows:

[0124] 1) The maximum and minimum output constraints of each unit and the energy storage system constraints are consistent with the models established by the microgrid and virtual power plant.

[0125] 2) Distribution network constraints

[0126] For any node i and branch ij:

[0127] Among them, equation (37) is the power balance constraint of each node, equations (38)-(41) are the active and reactive power limit constraints of the distribution network branch flow, and equation (42) is the node voltage range limit constraint.

[0128]

[0129]

[0130]

[0131] -P ij,max ≤P ij ≤P ij,max (40)

[0132] -Q ij,mjx ≤Q ij ≤Q ij,max (41)

[0133] U imin ≤U i ≤U imax (42)

[0134] Where P inject,i , Q inject,i are the active power and reactive power input to node i, NB is the total number of nodes, r ij 、x ij are the equivalent resistance and equivalent reactance of branch ij, V i , δ i are the amplitude and phase angle of the node voltage at node i, V j , δ j are the amplitude and phase angle of the node voltage at node j, P ij , Q ij are the active power and reactive power on branch ij, P ij,max , Q ij,maxis the maximum limit of active and reactive power flow of line ij, U imax , U imin are the upper and lower limits of the operating voltage of node i respectively.

[0135] In step S102, long-term parameter data of the target distribution network system and the target flexibility resources are obtained, and the long-term parameter data are input into the first mathematical model and the second mathematical model to calculate the long-term characteristic evaluation index.

[0136] like Figure 2 As shown, in the actual implementation process, the acquired long-term parameter data is input into the first mathematical model and the second mathematical model, the long-term characteristic evaluation indicators under the long-term parameters of the balance zone are calculated, and the negative indicators in the indicators are processed positively, wherein the long-term characteristic evaluation indicators include the distributed power supply and main grid power exchange rate, distributed power supply utilization rate and power supply reliability rate in the reliability indicators; the power balance degree and system inertial energy supply ratio in the stability indicators; the adjustable power range and climbing rate in the flexibility indicators; the power grid loss rate and demand response shortage ratio in the economic indicators; the self-generated and self-used power shortage ratio, the self-generated and self-used power surplus ratio and the energy storage power absorption capacity in the coordination indicators.

[0137] In step S103, an installed capacity plan of target flexibility resources is formulated according to the long-term characteristic evaluation index.

[0138] like Figure 2 As shown in the figure, in the actual implementation process, the month-on-month scoring method is used to weight the various characteristic evaluation indicators in the long-term characteristic evaluation indicators, and the scores of the five evaluation directions of reliability, stability, flexibility, economy and coordination are calculated according to the weights of each indicator. Then, according to the scores and specific actual needs, a reasonable operation mode is selected from the three operation modes of microgrid, virtual power plant, and source-grid-load-storage integration to plan the installed capacity of each generating unit.

[0139] In step S104, short-term parameter data of the target distribution network system and the target flexibility resource are obtained, and the short-term parameter data are input into the first mathematical model and the second mathematical model to calculate the short-term characteristic evaluation index.

[0140] In some embodiments, the short-term characteristic evaluation indicators include the equipment operating parameters, load conditions and corresponding transaction electricity price data of the target distribution network system, wherein the equipment operating parameters include the rated power of each generator set, operation and maintenance cost parameters, fuel combustion cost parameters, environmental governance cost parameters generated after fuel combustion, and the charging and discharging efficiency of the energy storage system and its rated capacity; special items of the short-term characteristic evaluation indicators include the power exchange rate between distributed power sources and the main grid, the power load adaptability and the grid loss rate.

[0141] Specifically, the parameter data of the target distribution network system and flexibility resources obtained include but are not limited to collecting the load conditions of the distribution network system and the corresponding transaction electricity price data and the operating parameters of the main equipment in the system, among which the main equipment operating parameters include the main equipment considering distributed conventional diesel generator sets, wind generator sets, photovoltaic generator sets and energy storage systems. The equipment operating parameters collected include but are not limited to the rated power of each generator set, operation and maintenance cost parameters, fuel combustion cost parameters, environmental governance cost parameters generated after fuel combustion, the charging and discharging efficiency of the energy storage system and its rated capacity.

[0142] Furthermore, the above short-term parameter data are respectively input into the first mathematical model and the second mathematical model to calculate the short-term characteristic evaluation index, wherein the short-term characteristic evaluation index includes a reliability index, a stability index, a flexibility index, an economic index and a coordination index, which are as follows:

[0143] (1) Reliability indicators include the power exchange rate between distributed power sources and the main grid, the power supply utilization rate of distributed power sources, and the power supply reliability rate, among which:

[0144] The electric energy exchange rate between distributed generation and main grid is used to reflect the electric energy exchange between the balancing area system and the main grid within a certain evaluation period. The calculation formula is:

[0145]

[0146] Where P S (t) is the sum of the active output of each micro-source in the system at time t, W M is the controllable load power within the system, in MWh, W L is the total internal load of the system, in MWh;

[0147] The power supply utilization rate of distributed generation is calculated by the ratio of the actual power generation of all DGs in the balancing area to their rated power generation. The calculation formula is:

[0148]

[0149] Where N is the number of DGs in the system, W G,i is the actual power generation of the ith DG, in MWh, is the rated power generation of the ith DG, in MWh;

[0150] The power supply reliability rate is used to reflect the proportion of the time during which the system provides power normally and stably during the statistical time. The calculation formula is:

[0151]

[0152] Where, T offis the average power outage time for users, T z The preset statistical time.

[0153] (2) Stability indicators include power supply load adaptability, proportion of adjustable power supply, power balance and system inertial energy supply proportion, among which:

[0154] The power load adaptability is used to reflect the balance between power generation capacity and power demand in the balancing area. The calculation formula is:

[0155]

[0156] Where P a is the total installed capacity of various power sources, P L,max is the maximum load of the balancing zone system;

[0157] The higher the proportion of adjustable power sources, the higher the proportion of controllable power sources in the energy composition of the system, which means that the system has more flexible scheduling and adjustment capabilities. Among them, controllable energy mainly includes controllable nuclear power units, coal-fired power units and energy storage systems, etc. The calculation formula is:

[0158]

[0159] Where P c is the installed capacity of the system’s adjustable power supply, P z,max is the total installed capacity;

[0160] Power balance is an indicator used to evaluate the degree of power balance in the power system. The calculation formula is:

[0161]

[0162] Where P in is the total input power, which is the sum of all input power in the system, P out is the total output power, which is the sum of all output power in the system.

[0163] The system inertia energy supply ratio refers to the system comprehensive inertia capacity after combining the electrical inertia, thermal inertia, etc. in the comprehensive energy system. It is used to alleviate the immediate imbalance of system energy supply and demand and reflect the system stability. The calculation formula is:

[0164]

[0165] Where W it is the total energy supply of the unit with energy supply inertia, W sp The total amount of energy supplied to the system.

[0166] (3) Flexibility indicators include adjustable power ratio and ramp rate, among which:

[0167] The adjustable power ratio refers to the ratio of the adjustable amplitude of the system output power amplitude to the maximum output of the system, which reflects the flexibility of the system in dealing with load changes, failures or other emergencies. The calculation formula is:

[0168]

[0169] Where P out,max , P out,min Respectively represent the maximum and minimum values ​​of the system output.

[0170] The ramp rate is calculated by the ratio of the maximum adjusted output value per minute to the rated capacity of the system. It describes the speed and efficiency of the system in responding to external changes. The calculation formula is:

[0171]

[0172] In the formula, Adjust the maximum output per minute, E con is the rated capacity of the system.

[0173] (4) Economic indicators include the power grid loss rate and the demand response power shortage ratio, among which:

[0174] The power grid loss rate refers to the proportion of total power loss during power transmission in a certain area to the total power supply. It is a commonly used key indicator reflecting the power supply management level of the power grid. Its calculation formula is:

[0175]

[0176] Where W Loss The power loss during transmission to the power grid, W z The unit of total power supply is MWh.

[0177] The demand response shortfall ratio represents the loss of users after participating in demand-side response within a certain evaluation period. The calculation formula is:

[0178]

[0179] Where W short,load The shortfall in load power after demand response is not met, W z,load is the total load demand electricity, the unit is MWh.

[0180] (5) Coordination indicators include the proportion of insufficient self-generated electricity for self-consumption, the proportion of surplus self-generated electricity for self-consumption, and the proportion of energy storage and consumption electricity, among which:

[0181] The shortfall ratio of self-generated and self-consumed electricity reflects the ratio of the shortfall of self-generated and self-consumed electricity relative to the total load to the total load electricity demand within a certain period of time. The calculation formula is:

[0182]

[0183] Where W short W is the amount of power that cannot be used to meet the load demand during the statistical period. z,Load It is the total load power demand during the statistical period.

[0184] The proportion of self-generated and self-used electricity surplus reflects the proportion of self-generated and self-used electricity surplus to the total load demand electricity when the system distributed power generation meets the total load demand electricity within a certain period of time. The calculation formula is:

[0185]

[0186] Where W Left is the remaining power for self-generation and self-use within a certain period of time, W z,Load It is the total load power demand during the statistical period.

[0187] The proportion of energy storage consumption reflects the proportion of energy storage charging in the remaining electricity after deducting load demand from self-generated electricity within a certain period of time. The calculation formula is:

[0188]

[0189] Where W charge is the energy storage charge during the statistical time, W Left It refers to the remaining electricity generated and consumed by oneself during the statistical period.

[0190] In step S105, the special items of the short-term characteristic evaluation indicators are used as feasibility criteria for the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in different types of balancing areas, and obtain multiple actual balancing area operation modes, among which the balancing area operation modes include virtual power plant operation mode, microgrid operation mode and source-grid-load-storage integrated operation mode.

[0191] In the actual implementation process, the embodiment of the present invention can preliminarily determine whether the target flexibility resource is suitable for operation in the virtual power plant operation mode according to the power exchange rate between the distributed power source and the main grid in the reliability index. If the power exchange rate between the distributed power source and the main grid is greater than 0, it means that the target flexibility resource can meet the load demand of the target distribution network system, and there is surplus electricity to trade with the grid to obtain income, which meets the basic conditions for the virtual power plant to participate in electricity market transactions to obtain income and can be operated in the virtual power plant operation mode. Otherwise, it means that it cannot, and the virtual power plant operation mode is excluded to obtain the first exclusion result;

[0192] Furthermore, it is also possible to preliminarily determine whether the target flexibility resource is suitable for operation in the microgrid operation mode according to the power load adaptability of the stability index. If the power load adaptability is greater than 1, it means that the internal power balance constraint of the microgrid is met and it can be operated in the microgrid operation mode. Otherwise, it cannot be operated, and the microgrid operation mode is excluded to obtain the second exclusion result.

[0193] Furthermore, it is also possible to preliminarily determine whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode based on the grid loss rate of the economic index. If the grid loss rate is much higher than 10%, it means that the target flexibility resource is in the source-grid-load-storage integrated operation mode. After considering the distribution network constraints, the economic efficiency cannot be guaranteed, the operation efficiency is low, and it is not suitable for operation in this way. The source-grid-load-storage integrated operation mode is excluded, and the third exclusion result is obtained. On the contrary, it means that after considering the distribution network constraints, the economic efficiency of the source-grid-load-storage integrated operation mode can be basically guaranteed, and it can be operated in the source-grid-load-storage integrated operation mode, and the safety and stability of the operation can be adjusted through this balancing area technology;

[0194] The first elimination result, the second elimination result and the third elimination result obtained through the above elimination process determine multiple actual balance zone operation modes.

[0195] In step S106, based on the installed capacity planning, the scheduling plans and operation results under multiple actual balancing area operation modes are obtained to formulate an optimized scheduling plan for the target flexibility resources.

[0196] Specifically, based on pre-planning, the embodiments of the present invention will comprehensively consider and compare the three aspects of economic benefits, new energy consumption, and safe and stable operation under different balancing area operation modes, so as to formulate and adjust the optimal scheduling plan for flexible resources that meets the expected requirements.

[0197] In step S107, the optimized scheduling plan of the target flexibility resources is input into the target distribution network system to determine whether the optimized scheduling plan of the target flexibility resources meets the preset safe operation requirements of the distribution network. If so, the optimized scheduling plan of the target flexibility resources is output as the final scheduling plan. Otherwise, a new optimized scheduling plan of the target flexibility resources is re-formulated until the preset safe operation requirements of the distribution network are met.

[0198] In the actual implementation process, the embodiment of the present invention inputs the optimal scheduling scheme of the target flexibility resource into the target distribution network system to obtain the voltage of each node and the power flow on the branch;

[0199] Determine whether the voltage of each node exceeds the first preset upper limit or is lower than the second preset lower limit, and whether the flow on the branch exceeds the third preset upper limit. If the voltage of each node exceeds the first preset upper limit and the flow on the branch exceeds the third preset upper limit, or if the voltage of each node is lower than the second preset upper limit and the flow on the branch exceeds the third preset upper limit, then the optimal scheduling plan of the target flexibility resource meets the preset safe operation requirements of the distribution network, and the optimal scheduling plan of the target flexibility resource is output as the final scheduling plan. Otherwise, iteratively execute steps S104-S105, and re-formulate the optimal scheduling plan for the new target flexibility resource according to the scheduling plans and operating results under multiple actual balancing area operation modes, and input it into the target distribution network system to determine whether the optimal scheduling plan for the new target flexibility resource meets the preset safe operation requirements of the distribution network until the preset safe operation requirements of the distribution network are met.

[0200] The flexible resource control method considering the differentiated characteristics of multiple balance zones proposed in the embodiment of the present invention is further described below through a specific embodiment.

[0201] like Figure 3 As shown in the figure, a 33-node distribution network system in a certain place mainly includes two conventional diesel generator sets, one photovoltaic unit and one wind turbine set, as well as one energy storage system (battery).

[0202] like Figure 4 and 5 As shown, the short-term parameter data of the target distribution network system and flexibility resources are obtained in advance. The short-term parameter data of the distribution network system mainly includes the following aspects.

[0203] The relevant operating parameters and other basic parameters of the main equipment in the system are shown in the following table.

[0204] Table 1 Basic parameters of equipment

[0205]

[0206] Table 2 Rated power of each unit

[0207] unit Rated power, MW unit Rated power, MW Photovoltaic unit 2 Wind turbines 2 Diesel Generator Unit 1 2 No. 2 diesel generator set 2

[0208] Table 3 Environmental governance cost parameters

[0209] Pollutant Type <![CDATA[Governance cost, ten thousand yuan·kg -1 > <![CDATA[Emission factor, kg·MWh -1 > NOX <![CDATA[2.754e -3 ]]> 8.662 SO2 <![CDATA[6.49e -4 ]]> 0.982 CO <![CDATA[1.12e -4 ]]> 4.64 CO2 <![CDATA[9.2e -6 ]]> 464.074

[0210] Table 4 Other basic parameters

[0211] project Specification project Specification project Specification Years of operation 10 years discount rate 5％ Simulation duration 24h

[0212] Table 5 Energy storage battery related parameters

[0213]

[0214]

[0215] The characteristic evaluation index parameters of the system obtained by calculation are shown in the following table.

[0216] Table 6 Feature evaluation index parameters

[0217]

[0218] Through the above basic parameters of the distribution network system and the corresponding characteristic evaluation index parameters, some basic properties of the studied system can be analyzed. First of all, the distributed resources considered in the system are mainly power sources and energy storage, and are mainly connected to the distribution network nodes in a large-scale centralized manner. Based on the characteristic evaluation index parameters of the distribution network system, it can be seen that the indicators of reliability, stability, flexibility and coordination are all at a relatively reasonable level, indicating that after the distribution network itself is connected to the resources, the power generation of the generator set can fully meet the load demand in the system and have a surplus, and can basically maintain reliable, stable and safe operation, but the economic indicators are poor and the power grid loss rate is high. In the following flexible resource optimization scheduling and comparative analysis, the basic properties of the distribution network system and the characteristics of different balancing area operation modes will be comprehensively considered, and the differences between different operation modes will be analyzed to draw the final conclusion.

[0219] Furthermore, the simulation scheduling of this specific embodiment uses the Cplex solver to perform optimization solution calculations.

[0220] (1) Microgrid dispatch simulation results and analysis

[0221] Table 7 Cost and benefits of microgrid dispatching scheme

[0222]

[0223]

[0224] Depend on Figure 6 , Figure 7 and Figure 8It can be seen that when the system power load is far lower than the sum of the wind turbine and photovoltaic output, and the output cost of new energy is significantly lower than the output of diesel units and batteries, when the flexible resources in the system are operated in the form of microgrids, wind energy and photovoltaics will be used first, that is, during the entire simulation time, wind turbines and photovoltaics use the "maximum power point tracking" mode to maintain maximum output. The 01:00-05:00 period is in the low power consumption period, and the wind turbine and diesel engine output sell electricity to the grid, and the surplus is used to charge the battery; the 05:00-16:00 period, the power load increases, and the photovoltaic unit becomes the output unit. After meeting the load, more power surplus is sold to the grid, and the remaining power continues to charge the battery; the 16:00-24:00 period, the photovoltaic unit output gradually decreases to 0, and the battery discharges to maintain stable output and continue to sell electricity to the grid. Throughout the day, the diesel generator sets produce stable power, and the power of photovoltaic and wind turbines is surplus while meeting the system load. The microgrid will transmit the surplus power to the large grid for profit or use it for battery charging and storage.

[0225] Depend on Fig. 9 It can be seen that after optimized scheduling, the SOC change of the energy storage system in the microgrid mode remains within a reasonable operating range; during the period of low electricity consumption and low electricity prices from 01:00 to 05:00, the energy storage is charged; during the period of 06:00 to 08:00, the load increases, the transaction price rises, and the energy storage is discharged, improving the economy of the microgrid by buying low and selling high. During the period of 09:00 to 15:00, the output of the photovoltaic unit increases significantly, and the energy storage is charged to store power; while during the period of 17:00 to 24:00, the photovoltaic output drops sharply, and the output of the energy storage system maintains the output balance of the entire system, effectively playing a role in balancing supply and demand in the optimized scheduling.

[0226] (2) Virtual power plant dispatch simulation results and analysis

[0227] Table 8 Cost and benefits of virtual power plant scheduling scheme

[0228] project Specification project Specification Wind power costs 1.8264 million yuan Photovoltaic costs 2.371 million yuan No. 1 Diesel Engine Cost 22.44356 million yuan No. 2 Diesel Engine Cost 26.30973 million yuan Energy storage costs 1.597425 million yuan Power purchase cost 0 income 105.9017 million yuan Net income 51.353585 million yuan

[0229] Depend on Fig.10 , Fig.11 , Fig.12 and Fig.13It can be seen that when the flexible resources in the above system are operated in the form of a virtual power plant, the changes in the transaction price of the power market have a very obvious impact on the total output of the system. Through observation and comparison, it can be seen that in the period of 01:00-05:00, the power price is at a low period, the total output of the virtual power plant is also at a low level, and the system tends to store more power in the form of energy storage; in the period of 05:00-13:00, the transaction price of the power market is in an upward stage and reaches a high level, and the total output of the virtual power plant also continues to rise and reaches a high level; in the period of 13:00-19:00, the transaction price drops, and the total output drops sharply; in the period of 19:00-21:00, the transaction price rises in a short period of time, and the total output of the virtual power plant also reflects an upward trend; in the period of 21:00-24:00, the transaction price falls, and the total output drops accordingly. Overall throughout the day, diesel generators were basically operating at full load or at a relatively high output, while wind and solar generators experienced a certain degree of wind and solar power curtailment in some periods of time due to the constraints of the reserved spare capacity of the virtual power plant system.

[0230] Depend on Fig.14 It can be seen that the energy storage system in the virtual power plant mode mainly accompanies the changes in the electricity price in the power market, and performs charging and discharging actions according to the total output demand of the system. In the period of 01:00-05:00, the electricity price is low, the total output demand is small, and most of the excess power is transmitted to the energy storage system for storage; in the period of 09:00-13:00, the electricity demand is large, the trading electricity price is at a peak, and the total output demand is large, so the energy storage system discharges output; in the period of 19:00-21:00, the electricity price rises in a short period of time, the total output demand is large, and the energy storage system discharges output. Analysis shows that in the virtual power plant operation mode, after optimized scheduling, the energy storage system meets the changing demand of total output caused by changes in trading electricity prices through charging and discharging actions, so as to obtain greater benefits from the electricity market.

[0231] (3) Simulation results and analysis of integrated dispatching of power source, grid, load and storage

[0232] Table 9 Cost and benefits of source-grid-load-storage integrated dispatching scheme

[0233] project Specification project Specification Wind power costs 1.8264 million yuan Photovoltaic costs 2.371 million yuan No. 1 Diesel Engine Cost 7.961301 yuan No. 2 Diesel Engine Cost 26.52355 million yuan Energy storage costs 1.597425 million yuan Power purchase cost 536,088 yuan income 35.1053 million yuan Net income -5.710464 million yuan

[0234] Depend on Fig.15 , Fig.16 and Fig.17It can be seen that when the flexible resources in the above system are operated in an integrated source-grid-load-storage manner, the total system output basically changes with the load demand. In the 01:00-05:00 period, the load demand is at a low point, the system output is at a low level, the line loss is small, and after the load requirements are met, the excess power is mainly used for energy storage charging and transmission to the grid; in the 05:00-20:00 period, the electricity demand is large and the electricity price is at a high level, then the system output is high, and the line loss increases. Excluding the load demand and line loss, the surplus power is transmitted to the grid to obtain revenue; in the 20:00-24:00 period, the load decreases, and the total system output decreases accordingly. Overall, due to the need to consider the distribution network line loss and meet the system load at the same time, the total output demand of the system is large, the wind and solar power generators basically operate at maximum power throughout the day, and the diesel generators operate at a stable output.

[0235] Depend on Fig.18 It can be seen that under the operation mode of the integrated source-grid-load-storage system, during the period of 01:00-05:00, the system load is low, the electricity price is low, and the line loss is small, so the energy storage system is in a charging state and stores excess power; while during the period of 05:00-22:00, the system load is at a high level, and the line loss of the distribution network is also high during this period, so the energy storage system discharges to ensure load supply while supplementing the power of the line loss, playing a role in maintaining the stable operation of the source-grid-load-storage system.

[0236] Depend on Fig.19 , Fig. 20 , Fig.21 It can be seen that under the dispatching conditions of the three operation modes, the node voltages in the distribution network in different periods are within a reasonable range, and there is no frequent node voltage over-limit situation. The highest node voltage in the case of source-grid-load-storage integrated dispatching occurs at node 14 (photovoltaic generator access point), and the lowest voltage is at node 30; the highest voltage in the case of virtual power plant dispatching occurs at node 22 (DG1 access point), and the lowest voltage is at node 33; the highest voltage in the case of microgrid dispatching occurs at node 20 (wind turbine access point), and the lowest voltage is at node 31. Through observation and comparison, it is found that the nodes with higher voltage in the distribution network are often the access points of distributed power sources, while the points with lower voltage generally appear at the remote nodes of the feeder in the network. The size of the node voltage of the distribution network is constrained by the network topology and is related to different dispatching methods and the load power of each node.

[0237] Depend on Fig. 22From the power flow analysis of line 1-2 under different dispatching modes, it can be seen that under the constraints of the distribution network, the dispatching results of different operating modes will not exceed the maximum current carrying capacity of the line, that is, there will be basically no network congestion in the process of power transmission across nodes by different flexibility resources. However, it can be observed that under the dispatching of virtual power plants, the line power flow in some periods is close to the limit value of the branch power flow, and there is a certain risk of branch power flow exceeding the limit, causing distribution network congestion.

[0238] Based on the above, from the perspective of economic benefits, the balancing area mainly obtains benefits by transmitting surplus electricity to the power grid under the condition of meeting the load. Therefore, from the perspective of benefits alone, various flexible resources should increase their output as much as possible under actual conditions. Virtual power plants can trade in the power market as participants in the power market. They are mainly profit-oriented. In addition to the constraints of the flexible resources themselves, they are subject to fewer constraints. They cooperate with the charging and discharging actions of the energy storage system to obtain the maximum benefits under the three operating modes; in the microgrid mode, the output of the system is mainly affected by the system power balance constraints. In order to ensure that the system can operate independently, the load and output in the system must be kept at the same level. In the calculation example, the situation that the wind and solar output is far greater than the load demand obviously affects the performance of the energy storage and other output units in the system, thereby limiting the overall output of the system; in the source-grid-load-storage integrated dispatching mode, the main factors affecting the system output are the constraints of the distribution network itself and its line losses. Affected by the two, the surplus electricity of the system is reduced, and the benefits obtained are not enough to meet the fuel and operation and maintenance costs of each generator set and energy storage system.

[0239] From the perspective of new energy consumption, in the microgrid and source-grid-load-storage integrated mode, new energy such as wind power and photovoltaics can basically be used first. After optimized scheduling, wind and solar power generating units all maintain maximum output. However, as a profit-oriented balancing area, the virtual power plant will have to consider the constraints of reserve capacity to mitigate the impact of the uncertainty of wind and solar output on the stability of the output of the balancing area. Therefore, when the output of the new energy unit is predicted to be too large, in order to ensure the proportion of reserve capacity, the virtual power plant will have a certain degree of wind and solar abandonment.

[0240] From the perspective of operational reliability, virtual power plants have the risk of exceeding network limits in certain time periods due to excessive output. The source-grid-load-storage integrated dispatching method can optimize dispatching by considering the constraints of the distribution network itself. The node voltage will not exceed the upper voltage limit, nor will it be lower than the lower voltage limit. The line flow is within a reasonable range and has a certain margin, and there will be no voltage limit or network congestion problems.

[0241] Therefore, in the situation discussed in this specific embodiment, the load demand is far less than the normal output of the output unit, which does not meet the requirements of maintaining power balance in the microgrid-type balancing area. The power balance constraint of the microgrid mode greatly limits the output and play of flexible resources other than wind and solar units; the source-grid-load-storage integrated operation mode can largely ensure the safe and stable operation of the distribution network, and can effectively avoid the frequent occurrence of voltage over-limit and blocking problems in the distribution network, but it also generates line losses, affects the total output of the system, and leads to poor economic benefits; the virtual power plant puts profit first, and the situation in the example where the load is far less than the output meets the profit needs of the virtual power plant. Although there are certain shortcomings and risks in the consumption of new energy and operational reliability, it is believed through observation and analysis that, on the one hand, the "abandoned" wind and solar power accounts for only a small part, and reducing a certain amount of wind and solar output within the controllable range can reduce the uncertainty of the system output, thereby improving the system stability. On the other hand, it can be seen from the voltage distribution and line flow under different scheduling conditions that for the excessive output of the virtual power plant in certain periods, the distribution network can withstand the corresponding impact with its relatively excellent network topology structure, thereby ensuring the safe and stable operation of the system. Therefore, considering all factors, it is recommended that flexible resources be operated in the form of virtual power plants, which can obtain maximum benefits under the premise of safe operation.

[0242] In summary, according to the flexibility resource control method considering the differentiated characteristics of multiple balancing areas proposed in the embodiment of the present invention, on the one hand, a variety of balancing area technologies are used to optimize the scheduling of flexibility resources, thereby improving the operating efficiency and flexibility of the distribution network system, and by accurately evaluating the characteristics of each balancing area, the optimal allocation of resources is achieved, and energy waste is reduced; on the other hand, through the balancing area characteristic evaluation indicators, those balancing area modes that cannot be effectively operated due to their own characteristic constraints are preliminarily excluded, effectively avoiding the unreasonable allocation of resources and system risks, and maintaining the stability and security of the distribution network; in addition, the scheduling plans and operating results under different balancing area operation modes are output, providing decision makers with comprehensive data support, helping to make scientific decisions and optimize operation strategies.

[0243] Next, a flexible resource control device considering differentiated characteristics of multiple balancing areas according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0244] Fig.23 It is a block diagram of a flexible resource control device considering differentiated characteristics of multiple balancing areas according to an embodiment of the present invention.

[0245] like Fig.23 As shown, the flexibility resource control device 230 that considers the differentiated characteristics of multiple balance zones includes: an establishment module 2301, a first calculation module 2302, a first formulation module 2303, a second calculation module 2304, an exclusion module 2305, a second formulation module 2306 and a judgment module 2307.

[0246] Among them, the establishment module 2301 is used to establish the first mathematical model of the target flexibility resource and the second mathematical model of different types of balancing areas respectively. The first calculation module 2302 is used to obtain the long-term parameter data of the target distribution network system and the target flexibility resource, and input the long-term parameter data into the first mathematical model and the second mathematical model to calculate the long-term characteristic evaluation index. The first formulation module 2303 is used to formulate the installed capacity planning of the target flexibility resource according to the long-term characteristic evaluation index. The second calculation module 2304 is used to obtain the short-term parameter data of the target distribution network system and the target flexibility resource, and input the short-term parameter data into the first mathematical model and the second mathematical model to calculate the short-term characteristic evaluation index. The exclusion module 2305 is used to use the special items of the short-term characteristic evaluation index as the feasibility criterion of the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in different types of balancing areas, and obtain multiple actual balancing area operation modes, wherein the balancing area operation mode includes the virtual power plant operation mode, the microgrid operation mode and the source-grid-load-storage integrated operation mode. The second formulation module 2306 is used to obtain the scheduling scheme and operation effect under multiple actual balancing area operation modes based on the installed capacity planning, so as to formulate the optimized scheduling scheme of the target flexibility resource. Judgment module 2307 is used to input the optimized scheduling plan of the target flexibility resources into the target distribution network system to determine whether the optimized scheduling plan of the target flexibility resources meets the preset safe operation requirements of the distribution network. If so, the optimized scheduling plan of the target flexibility resources is output as the final scheduling plan. Otherwise, a new optimized scheduling plan of the target flexibility resources is re-formulated until the preset safe operation requirements of the distribution network are met.

[0247] In some embodiments, the short-term characteristic evaluation index includes at least one of a reliability index, a stability index, a flexibility index, an economic index, and a coordination index, wherein:

[0248] Reliability indicators include the power exchange rate between distributed power sources and the main grid, the power supply utilization rate of distributed power sources and the power supply reliability rate;

[0249] Stability indicators include power supply load adaptability, proportion of adjustable power supply, power balance and system inertial energy supply proportion;

[0250] Flexibility indicators include adjustable power range and ramp rate;

[0251] Economic indicators include the power grid loss rate and the proportion of demand response power shortage;

[0252] Coordination indicators include the shortfall ratio of self-generated and self-consumed electricity, the surplus ratio of self-generated and self-consumed electricity, and the energy storage capacity to absorb electricity.

[0253] Special items of short-term characteristic evaluation indicators include the power exchange rate between distributed generation and main grid, power load adaptability and grid loss rate.

[0254] In some embodiments, the exclusion module 2305 includes:

[0255] The first exclusion unit is used to preliminarily determine whether the target flexible resource is suitable for operation in the virtual power plant operation mode according to the power exchange rate between the distributed power source and the main grid in the reliability index. If the power exchange rate between the distributed power source and the main grid is greater than 0, the target flexible power generation resource meets the load demand of the target distribution network system, and there is surplus electricity to trade with the grid to obtain income, which meets the basic conditions for the virtual power plant to participate in the power market transaction to obtain income and can be operated in the virtual power plant operation mode. Otherwise, the operation mode of the virtual power plant is excluded to obtain the first exclusion result;

[0256] The second exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the microgrid operation mode according to the power load adaptability of the stability index. If the power load adaptability is greater than 1, it meets the internal power balance constraint of the microgrid and can be operated in the microgrid operation mode. Otherwise, the microgrid operation mode is excluded to obtain a second exclusion result;

[0257] The third exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode according to the power grid loss rate of the economic index. If the power grid loss rate is higher than 10%, it means that the target flexibility resource is in the source-grid-load-storage integrated operation mode. After considering the distribution network constraints, the economic efficiency cannot be guaranteed. Then the source-grid-load-storage integrated operation mode is excluded to obtain the third exclusion result. On the contrary, the economic efficiency of the source-grid-load-storage integrated operation mode can be basically guaranteed, and the target flexibility resource can be operated in the source-grid-load-storage integrated operation mode.

[0258] The determination unit is used to determine a plurality of actual balancing zone operation modes according to the first exclusion result, the second exclusion result and the third exclusion result.

[0259] In some embodiments, the determination module 2307 includes:

[0260] An acquisition unit is used to input the optimal dispatching scheme of the target flexibility resource into the target distribution network system to obtain the voltage of each node and the power flow on the branch;

[0261] A judgment unit is used to judge whether the voltage of each node exceeds a first preset upper limit or is lower than a second preset lower limit, and whether the flow on the branch exceeds a third preset upper limit. If the voltage of each node exceeds the first preset upper limit and the flow on the branch exceeds the third preset upper limit, or if the voltage of each node is lower than the second preset upper limit and the flow on the branch exceeds the third preset upper limit, then the optimal scheduling plan of the target flexibility resource meets the preset safe operation requirements of the distribution network, and the optimal scheduling plan of the target flexibility resource is output as the final scheduling plan. Otherwise, according to the scheduling plans and operating results under multiple actual balancing area operation modes, a new optimal scheduling plan for the flexibility resource is re-formulated and input into the target distribution network system to judge whether the new optimal scheduling plan for the target flexibility resource meets the preset safe operation requirements of the distribution network, and the formulation and judgment process is iteratively executed until the preset safe operation requirements of the distribution network are met.

[0262] It should be noted that the above explanation of the embodiment of the flexible resource control method considering the differentiated characteristics of multiple balancing zones is also applicable to the flexible resource control device considering the differentiated characteristics of multiple balancing zones of this embodiment, and will not be repeated here.

[0263] According to the flexibility resource control device that takes into account the differentiated characteristics of multiple balancing areas proposed in the embodiment of the present invention, on the one hand, multiple balancing area technologies are used to optimize the scheduling of flexibility resources, thereby improving the operating efficiency and flexibility of the distribution network system, and by accurately evaluating the characteristics of each balancing area, the optimal allocation of resources is achieved, and energy waste is reduced; on the other hand, through the balancing area characteristic evaluation indicators, those balancing area modes that cannot be effectively operated due to their own characteristic constraints are preliminarily excluded, effectively avoiding unreasonable allocation of resources and system risks, and maintaining the stability and security of the distribution network; in addition, the scheduling plans and operating results under different balancing area operation modes are output, providing decision makers with comprehensive data support, helping to make scientific decisions and optimize operation strategies.

[0264] Fig.24 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0265] A memory 2401 , a processor 2402 , and a computer program stored in the memory 2401 and executable on the processor 2402 .

[0266] When the processor 2402 executes the program, the flexible resource control method considering the differentiated characteristics of the multiple balance areas provided in the above embodiment is implemented.

[0267] Furthermore, the electronic device also includes:

[0268] The communication interface 2403 is used for communication between the memory 2401 and the processor 2402 .

[0269] The memory 2401 is used to store computer programs that can be executed on the processor 2402 .

[0270] The memory 2401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0271] If the memory 2401, the processor 2402 and the communication interface 2403 are implemented independently, the communication interface 2403, the memory 2401 and the processor 2402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.24 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0272] Optionally, in a specific implementation, if the memory 2401, the processor 2402 and the communication interface 2403 are integrated on a chip, the memory 2401, the processor 2402 and the communication interface 2403 can communicate with each other through an internal interface.

[0273] The processor 2402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0274] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned flexibility resource control method considering the differentiated characteristics of multiple balance zones.

[0275] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0276] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0277] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0278] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0279] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0280] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0281] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0282] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A flexible resource control method considering the differentiated characteristics of multiple balance zones, characterized in that: The following steps are involved: Establish a first mathematical model of target flexibility resources and a second mathematical model of different types of balancing areas respectively, wherein the first mathematical model of the target flexibility resources includes the operating cost of wind turbines, the operating cost of photovoltaic generators, the operating cost of diesel generators and the operating cost of energy storage systems, and the second mathematical models of different types of balancing areas include the optimization model of microgrid operation mode and its constraints, the optimization model of virtual power plant operation mode and its constraints, and the optimization model of source-grid-load-storage integrated operation mode and its constraints; Acquire long-term parameter data of the target distribution network system and the target flexibility resource, and input the long-term parameter data into the first mathematical model and the second mathematical model to calculate a long-term characteristic evaluation index; Formulate an installed capacity plan for the target flexibility resource according to the long-term characteristic evaluation index; Acquire short-term parameter data of the target distribution network system and the target flexibility resource, and input the short-term parameter data into the first mathematical model and the second mathematical model to calculate a short-term characteristic evaluation index; The special items of the short-term characteristic evaluation index are used as feasibility criteria for the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and multiple actual balancing area operation modes are obtained, wherein the balancing area operation modes include a virtual power plant operation mode, a microgrid operation mode and a source-grid-load-storage integrated operation mode; Based on the installed capacity planning, obtaining the scheduling plans and operation effects under the multiple actual balancing area operation modes to formulate an optimized scheduling plan for the target flexibility resources; The optimized scheduling plan of the target flexibility resources is input into the target distribution network system to determine whether the optimized scheduling plan of the target flexibility resources meets the preset safe operation requirements of the distribution network. If so, the optimized scheduling plan of the target flexibility resources is output as the final scheduling plan. Otherwise, a new optimized scheduling plan of the target flexibility resources is re-formulated until the preset safe operation requirements of the distribution network are met.

2. The flexibility resource control method considering the differentiated characteristics of multiple balance zones according to claim 1 is characterized in that: The short-term characteristic evaluation index includes at least one of a reliability index, a stability index, a flexibility index, an economic index and a coordination index, wherein: The reliability indicators include the power exchange rate between distributed power sources and the main grid, the power supply utilization rate of distributed power sources and the power supply reliability rate; The stability indicators include power supply load adaptability, proportion of adjustable power supply, power balance and system inertial energy supply proportion; The flexibility indicators include adjustable power range and climbing rate; The economic indicators include power grid loss rate and demand response shortfall ratio; The coordination indicators include the shortfall ratio of self-generated and self-consumed electricity, the surplus ratio of self-generated and self-consumed electricity and the energy storage capacity for absorbing electricity; The special items of the short-term characteristic evaluation index include the power exchange rate between the distributed power source and the main grid, the power source load adaptability and the grid loss rate.

3. The flexibility resource control method considering the differentiated characteristics of multiple balance zones according to claim 2 is characterized in that: The special items of the short-term characteristic evaluation index are used as feasibility criteria for the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and multiple actual balancing area operation modes are obtained, including: Preliminarily determine whether the target flexibility resource is suitable for operation in the virtual power plant operation mode according to the distributed power source and main grid power exchange rate in the reliability index; if the distributed power source and main grid power exchange rate is greater than 0, the target flexibility power generation resource meets the load demand of the target distribution network system, and has surplus electricity to trade with the grid to obtain income, and meets the basic conditions for the virtual power plant to participate in electricity market transactions to obtain income, and can be operated in the virtual power plant operation mode; otherwise, the operation mode of the virtual power plant is excluded, and a first exclusion result is obtained; Preliminarily determining whether the target flexibility resource is suitable for operation in the microgrid operation mode according to the power load adaptability of the stability index; if the power load adaptability is greater than 1, the internal power balance constraint of the microgrid is met and the microgrid operation mode can be operated; otherwise, the microgrid operation mode is excluded to obtain a second exclusion result; According to the power grid loss rate of the economic index, it is preliminarily determined whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode. If the power grid loss rate is higher than 10%, it means that the economic efficiency of the target flexibility resource cannot be guaranteed under the source-grid-load-storage integrated operation mode after considering the distribution network constraints. Then the source-grid-load-storage integrated operation mode is excluded to obtain a third exclusion result. On the contrary, the economic efficiency of the source-grid-load-storage integrated operation mode can be basically guaranteed and the target flexibility resource can be operated in the source-grid-load-storage integrated operation mode. The plurality of actual balancing zone operating modes are determined according to the first exclusion result, the second exclusion result, and the third exclusion result.

4. The flexibility resource control method considering the differentiated characteristics of multiple balance zones according to claim 1 is characterized in that: The optimized scheduling scheme of the target flexibility resource is input into the target distribution network system to determine whether the optimized scheduling scheme of the target flexibility resource meets the preset distribution network safety operation requirements. If so, the optimized scheduling scheme of the target flexibility resource is output as the final scheduling scheme. Otherwise, a new optimized scheduling scheme of the target flexibility resource is re-formulated until the preset distribution network safety operation requirements are met, including: Inputting the optimal dispatching scheme of the target flexibility resource into the target distribution network system to obtain the voltage of each node and the power flow on the branch; Determine whether the voltage of each node exceeds the first preset upper limit or is lower than the second preset lower limit, and whether the power flow on the branch exceeds the third preset upper limit. If the voltage of each node exceeds the first preset upper limit and the power flow on the branch exceeds the third preset upper limit, or if the voltage of each node is lower than the second preset upper limit and the power flow on the branch exceeds the third preset upper limit, then the optimal scheduling plan of the target flexibility resource meets the preset safe operation requirements of the distribution network, and the optimal scheduling plan of the target flexibility resource is output as the final scheduling plan. Otherwise, according to the scheduling plans and operating results under the multiple actual balancing area operation modes, a new optimal scheduling plan for the flexibility resource is re-formulated and input into the target distribution network system to determine whether the optimal scheduling plan of the new target flexibility resource meets the preset safe operation requirements of the distribution network, and iterate the formulation and judgment process until the preset safe operation requirements of the distribution network are met.

5. A flexible resource control device considering the differentiated characteristics of multiple balance zones, characterized in that: include: Establishing a module for respectively establishing a first mathematical model of a target flexibility resource and a second mathematical model of different types of balancing areas, wherein the first mathematical model of the target flexibility resource includes the operating cost of a wind turbine generator set, the operating cost of a photovoltaic generator set, the operating cost of a diesel generator set and the operating cost of an energy storage system, and the second mathematical model of different types of balancing areas includes an optimization model of a microgrid operation mode and its constraints, an optimization model of a virtual power plant operation mode and its constraints, and an optimization model of a source-grid-load-storage integrated operation mode and its constraints; a first calculation module, configured to obtain long-term parameter data of a target distribution network system and the target flexibility resource, and input the long-term parameter data into the first mathematical model and the second mathematical model to calculate a long-term characteristic evaluation index; A first formulation module, used to formulate an installed capacity plan of the target flexibility resource according to the long-term characteristic evaluation index; a second calculation module, configured to obtain short-term parameter data of the target distribution network system and the target flexibility resource, and input the short-term parameter data into the first mathematical model and the second mathematical model to calculate a short-term characteristic evaluation index; An exclusion module is used to use the special items of the short-term characteristic evaluation index as the feasibility criterion of the balancing area operation mode to exclude the balancing area operation modes that cannot be operated in the different types of balancing areas, and obtain multiple actual balancing area operation modes, wherein the balancing area operation modes include a virtual power plant operation mode, a microgrid operation mode and a source-grid-load-storage integrated operation mode; A second formulation module is used to obtain the scheduling plans and operation effects under the multiple actual balancing area operation modes based on the installed capacity planning, so as to formulate an optimized scheduling plan for the target flexibility resources; A judgment module is used to input the optimized scheduling plan of the target flexibility resources into the target distribution network system to determine whether the optimized scheduling plan of the target flexibility resources meets the preset safe operation requirements of the distribution network. If so, the optimized scheduling plan of the target flexibility resources is output as the final scheduling plan; otherwise, a new optimized scheduling plan of the target flexibility resources is re-formulated until the preset safe operation requirements of the distribution network are met.

6. The flexibility resource control device considering the differentiated characteristics of multiple balance zones according to claim 5 is characterized in that: The short-term characteristic evaluation index includes at least one of a reliability index, a stability index, a flexibility index, an economic index and a coordination index, wherein: The reliability indicators include the power exchange rate between distributed power sources and the main grid, the power supply utilization rate of distributed power sources and the power supply reliability rate; The stability indicators include power supply load adaptability, proportion of adjustable power supply, power balance and system inertial energy supply proportion; The flexibility indicators include adjustable power range and climbing rate; The economic indicators include power grid loss rate and demand response shortfall ratio; The coordination indicators include the shortfall ratio of self-generated and self-consumed electricity, the surplus ratio of self-generated and self-consumed electricity and the energy storage capacity for absorbing electricity; The special items of the short-term characteristic evaluation index include the power exchange rate between the distributed power source and the main grid, the power source load adaptability and the grid loss rate.

7. The flexibility resource control device considering the differentiated characteristics of multiple balance zones according to claim 6 is characterized in that: The exclusion module includes: The first exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the virtual power plant operation mode according to the power exchange rate between the distributed power source and the main grid in the reliability index. If the power exchange rate between the distributed power source and the main grid is greater than 0, the target flexibility power generation resource meets the load demand of the target distribution network system, and there is surplus electricity to trade with the grid to obtain income, which meets the basic conditions for the virtual power plant to participate in electricity market transactions to obtain income and can be operated in the virtual power plant operation mode. Otherwise, the operation mode of the virtual power plant is excluded to obtain the first exclusion result; A second exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the microgrid operation mode according to the power load adaptability of the stability index. If the power load adaptability is greater than 1, the internal power balance constraint of the microgrid is met and the microgrid operation mode can be operated. Otherwise, the microgrid operation mode is excluded to obtain a second exclusion result. The third exclusion unit is used to preliminarily determine whether the target flexibility resource is suitable for operation in the source-grid-load-storage integrated operation mode according to the grid loss rate of the economic index. If the grid loss rate is higher than 10%, it means that the target flexibility resource cannot be economically guaranteed under the source-grid-load-storage integrated operation mode after considering the distribution network constraints. Then the source-grid-load-storage integrated operation mode is excluded to obtain a third exclusion result. Otherwise, the economy of the source-grid-load-storage integrated operation mode can be basically guaranteed and the target flexibility resource can be operated in the source-grid-load-storage integrated operation mode. A determination unit is used to determine the multiple actual balancing zone operation modes according to the first exclusion result, the second exclusion result and the third exclusion result.

8. The flexibility resource control device considering the differentiated characteristics of multiple balance zones according to claim 7 is characterized in that: The judging module comprises: An acquisition unit, used for inputting the optimal dispatching scheme of the target flexibility resource into the target distribution network system to obtain the voltage of each node and the power flow on the branch; A judgment unit is used to judge whether the voltage of each node exceeds a first preset upper limit or is lower than a second preset lower limit, and whether the power flow on the branch exceeds a third preset upper limit. If the voltage of each node exceeds the first preset upper limit and the power flow on the branch exceeds the third preset upper limit, or if the voltage of each node is lower than the second preset upper limit and the power flow on the branch exceeds the third preset upper limit, then the optimal scheduling scheme of the target flexibility resource meets the preset safe operation requirements of the distribution network, and the optimal scheduling scheme of the target flexibility resource is output as the final scheduling scheme. Otherwise, according to the scheduling schemes and operating results under the multiple actual balancing area operation modes, a new optimal scheduling scheme for the flexibility resource is re-formulated and input into the target distribution network system to judge whether the new optimal scheduling scheme for the target flexibility resource meets the preset safe operation requirements of the distribution network, and the formulation and judgment process is iteratively executed until the preset safe operation requirements of the distribution network are met.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the flexible resource regulation method considering the differentiated characteristics of multiple balance zones as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a flexible resource control method taking into account differentiated characteristics of multiple balance zones as described in any one of claims 1 to 4.

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