An inertia auxiliary service configuration method considering participation of new market subjects

Abstract

This invention discloses an inertia ancillary service allocation method considering the participation of new market players, belonging to the field of power market optimization technology. The method first constructs a minimum inertia demand model to obtain the inertia demand of the system at different time periods. Second, for new market players, it comprehensively evaluates the power margin, dynamic response characteristics, and continuous energy storage support capacity of their internal resource units to accurately calculate the virtual inertia supply capacity. Then, based on the inertia retrofit cost, operating losses, and energy reservation coefficient, it calculates the unit cost and determines the inertia bidding price and lower limit for each player. Next, it establishes and solves the inertia ancillary service market clearing model to obtain the inertia winning bid and clearing price for each player. Finally, it generates an inertia dispatch execution plan based on the winning bid. This invention coordinates the hard constraints of system frequency security with the economics of multiple players, achieving optimized allocation of inertia resources and ensuring effective physical support when the power grid faces power disturbances.

Description

Technical Field

[0001] This invention belongs to the field of power market optimization technology, specifically relating to an inertia ancillary service configuration method that takes into account the participation of new market players. Background Technology

[0002] With the large-scale integration of high-proportion new energy sources and power electronic equipment, the power system is continuously evolving from a traditional synchronous machine-dominated form to a high-proportion power electronic form. As a result, the system's synchronous inertia level is constantly decreasing, and frequency stability issues are becoming increasingly prominent. Traditional synchronous generators can rely on rotating components to naturally provide inertial response, while new market players such as wind power, photovoltaics, energy storage, and virtual power plants usually need to provide virtual inertia support through additional control strategies.

[0003] Existing inertia auxiliary service configuration methods are mostly based on the inherent inertia of synchronous generator units, or only perform static estimations of virtual inertia capabilities. These methods fail to fully reflect the differences in power margin, state of charge, dynamic response delay, and continuous support capabilities of new market players under different operating conditions. Furthermore, the provision of inertia resources often involves investment in control system upgrades, operational losses, and opportunity costs in the electricity market. Without a reasonable pricing method, it is difficult to create effective market incentives.

[0004] Therefore, there is an urgent need to propose a configuration method that unifies and couples power system frequency security constraints, virtual inertia supply capacity assessment, and inertia ancillary service market prices. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide an inertia-assisted service configuration method that considers the participation of new market entities, thereby solving the problems in existing technologies.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for configuring inertia-assisted services that considers the participation of new market players includes the following steps: Construct a minimum inertia demand model for the power system to obtain the minimum inertia demand for the power system at different time periods; For internal resource units targeting new market entities, the virtual inertia supply capacity of each resource unit and each entity is calculated based on the power margin, dynamic response characteristics, and continuous support capacity of the energy storage resource unit. Based on the inertia function modification cost, single response operation cost and energy reservation coefficient of each resource unit, the unit inertia cost of the resource unit is determined, and based on the unit inertia cost, the lower limit of the inertia declaration price and the inertia declaration price for each subject to participate in the configuration are determined. A market clearing model for inertia auxiliary services is established. Based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price, and inertia bid price, the model is solved to obtain the inertia winning bid volume of each entity and determine the market clearing price. Based on the inertia scalar values ​​of each entity, an inertia auxiliary service call execution plan for the power system in the corresponding time period is generated.

[0007] Furthermore, the process of obtaining the minimum inertia requirement of the power system for each time period includes: Calculate the minimum inertia requirement under the constraint of the lowest frequency point to prevent triggering low-frequency load shedding protection, under the operating condition where the power system inertia level remains constant. Calculate the minimum inertia requirement under the frequency change rate constraint based on the rated frequency of the power system, the upper limit of the frequency change rate of the power system, and the unbalanced power faced by the power system. The maximum value of the minimum inertia requirement under the constraint of the lowest frequency point and the minimum inertia requirement under the constraint of the frequency change rate is taken as the minimum inertia requirement of the power system for each time period.

[0008] Furthermore, when calculating the virtual inertia supply capacity based on the aforementioned dynamic response characteristics, the dynamic effectiveness coefficient of the resource unit is calculated using the following formula. : In the formula, The effective duration of inertia; The equivalent delay time for the inertia response of resource unit x; The rate limiting or clipping reduction factor for resource unit x; The control mode reduction factor for resource unit x.

[0009] Furthermore, when the internal resource units of new market entities include energy storage resources, the process of calculating virtual inertia supply capacity includes: The difference between the maximum discharge power of the energy storage resource and the planned discharge amount for the corresponding time period is used as the power margin of the energy storage resource. Based on the discharge efficiency, current state of charge, allowable state of charge limit, and rated capacity of the energy storage resources, calculate the effective available energy of the energy storage resources for inertial response. Determine whether the effective available energy is greater than or equal to the product of the power margin and the effective duration of inertia. If yes, the sustainability coefficient is set to 1. If no, the ratio of the effective available energy to the product is used as the sustainability coefficient characterizing the continuous support capability. The virtual inertia supply capacity of the energy storage resource is obtained by multiplying its equivalent inertia time constant, persistence coefficient, power margin, and dynamic effectiveness coefficient.

[0010] Furthermore, when the internal resource units of new market entities include wind power or photovoltaic resources, the process of calculating virtual inertia supply capacity includes: Obtain the predicted and planned power output values ​​of wind power or photovoltaic resources for the corresponding time period, and use the difference between the predicted and planned power output values ​​as the power support margin. The virtual inertia supply capacity of wind power or photovoltaic resources is obtained by multiplying the equivalent inertia time constant of the wind power or photovoltaic resources, the power support margin, and the dynamic effectiveness coefficient.

[0011] Furthermore, when the internal resource unit includes energy storage resources, the process for determining the single-response operating cost includes: Based on the maximum allowable frequency deviation of the power system, the rated frequency of the power system, and the maximum discharge power of the energy storage resources, calculate the energy released in a single inertial response; Using the total energy generated over the entire lifespan of the energy storage resource, the depth of charge and discharge of the internal battery, the charge and discharge efficiency, and the number of charge and discharge cycles over the entire lifespan, the released energy is converted into the equivalent number of cycles for a single inertial response. The ratio of the equivalent number of cycles to the number of charge-discharge cycles is multiplied by the initial investment in the energy storage resource to obtain the single-response operating cost of the energy storage resource.

[0012] Furthermore, the process of determining the lower limit of the inertia declaration price and the inertia declaration price for each participating entity includes: For a new market entity composed of multiple heterogeneous resource units, extract the bids of each resource unit within the entity that can participate in inertia support; An internal resource unit price aggregation strategy is adopted, and the highest price among the extracted resource unit prices is used as the lower limit of the inertia bid price for the entity in the corresponding time period.

[0013] Furthermore, the market clearing model is a two-layer model, considering independent energy storage power stations (ES), new energy distribution and storage consortia (RES), and virtual power plants (DG). The upper-level model uses the maximization of the inertia market returns of each new market entity at the upper level as its objective function: In the formula, T represents the total number of time periods within the scheduling cycle. Trading hours For the group of participants in the inertia market, The total inertia revenue for participants in the inertia market during the scheduling cycle. The clearing price of the inertia market during time period t; as the main body The scalar value of inertia in time period t; as the main body The basic cost per unit of inertia; The lower-level model uses the minimum total cost of power system inertia procurement as its objective function: In the formula, as the main body Inertia service application price This represents the total cost of inertia procurement.

[0014] An inertia-assisted service configuration system that considers the participation of new market players, executing the above method, includes: Demand estimation module: Constructs a minimum inertia demand model for the power system to obtain the minimum inertia demand for the power system at different time periods; Supply capacity calculation module: For the internal resource units of new market entities, based on the power margin, dynamic response characteristics of the resource units, and the continuous support capacity for energy storage resource units, the module calculates the virtual inertia supply capacity of each resource unit and each entity. Price determination module: Based on the inertia function modification cost, single response operation cost and energy reservation coefficient of each resource unit, the unit inertia cost of the resource unit is determined, and based on the unit inertia cost, the lower limit of the inertia declaration price and the inertia declaration price of each subject participating in the configuration are determined. Market Clearing Module: Establish an inertia auxiliary service market clearing model, and solve it based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price and inertia bid price to obtain the inertia winning bid quantity of each entity and determine the market clearing price. Execution plan generation module: Generates the inertia auxiliary service call execution plan of the power system for the corresponding time period based on the inertia benchmark of each subject.

[0015] An electronic device includes: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform an operation corresponding to the inertia-assisted service configuration method that takes into account the participation of new market entities, as described above.

[0016] The beneficial effects of this invention are: 1. When constructing the minimum inertia requirement model of the system, this invention does not use a single index, but simultaneously calculates the minimum inertia requirement under the constraint of the rate of change of frequency (limited by the upper limit of the maximum rate of change) and the minimum inertia requirement under the constraint of the lowest frequency point (a threshold set to prevent triggering the low-frequency load shedding protection), and takes the maximum value of the two as the final requirement. Through the above-mentioned dual-constraint modeling method, the frequency safety red line of the system's bottom layer is directly linked to the inertia requirement, which can more accurately quantify the true minimum inertia requirement of the system under various unbalanced power disturbance conditions, thereby effectively avoiding the risk of frequency drop due to underestimation of the requirement.

[0017] 2. This invention delves into the physical control link of the converter when calculating the virtual inertia supply capacity. For all new entities, a "dynamic effectiveness coefficient" is introduced for reduction, which includes the equivalent delay of the frequency measurement-filtering-control link and the current limiting or clipping constraints of the converter. For energy storage resources, a sustainability coefficient limited by the state of charge (SOC) and the effective available energy is further introduced. By transforming objective physical limitations such as response delay, hardware current limiting, and battery depletion into specific mathematical reduction coefficients, the overestimation of the virtual inertia capacity on paper is avoided, and the actual available inertia level of different entities such as wind power, photovoltaics, and energy storage under specific operating conditions can be more realistically reflected.

[0018] 3. This invention establishes a pricing model based on multidimensional costs. This model not only calculates the basic inertia function modification investment and the hardware aging operation cost caused by a single response (e.g., calculating energy storage loss based on discharge depth and cycle count), but also creatively introduces an energy reservation coefficient to multiply and correct the basic cost price. By introducing the energy reservation coefficient, the implicit opportunity cost of the entity occupying the electricity market revenue due to reserved power margin is made explicit, thereby providing a reasonable economic compensation benchmark for each resource unit, significantly improving the rationality and interpretability of market price signals, and helping to stimulate the enthusiasm of new entities to participate in inertia support.

[0019] 4. This invention constructs a two-layer inertia auxiliary service market clearing model; the upper-layer model allows each new market participant to submit applications with the goal of maximizing their own inertia service revenue; the lower-layer model, from the dispatching side, aims to minimize the system's inertia procurement cost and is strictly constrained by the system's minimum inertia demand shortfall; this two-layer architecture deeply couples the system's frequency security hard constraints, the micro-operational state of new market participants, and the market price formation process in economics; the dual variable obtained from the solution serves as a unified clearing price, which can better coordinate individual profit-seeking demands with the overall power grid security defense. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the inertia-assisted service configuration method of the present invention; Figure 2 This is the result of the market clearing of electrical energy in this invention; Figure 3 This invention relates to the market clearing price of inertia and the winning bids for inertia by each entity; Figure 4 This invention provides an analysis of the market revenue of the inertia of each entity. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 like Figure 1 As shown, an inertia ancillary service configuration method considering the participation of new market players, applied to the power system, includes the following steps: Step 1: Construct a minimum inertia demand model for the power system to obtain the minimum inertia demand for each time period of the power system. In this embodiment, the power system includes synchronous generator units, new market entities, load-side power consumption units, a dispatching master station, and power electronic interface control devices connected to each entity. The synchronous generator units are used to provide basic synchronous inertia and conventional active power support. The new market entities include independent energy storage power stations, new energy distribution and storage consortia, and power source-type virtual power plants. The dispatching master station is used to obtain the operating status of each entity and generate an inertia auxiliary service call execution plan according to the method of the present invention. The converter control unit of each entity outputs the corresponding virtual inertia support power after a disturbance occurs according to the call execution plan.

[0024] The minimum inertia requirement of a power system is jointly determined by the inertia requirement corresponding to the frequency change rate constraint and the inertia requirement corresponding to the frequency minimum point constraint. a. Minimum inertia requirement under the constraint of lowest frequency point Under operating conditions where the grid inertia level remains constant, to prevent underfrequency load shedding protection from being triggered due to insufficient inertia support after a disturbance, it is necessary to ensure that the minimum frequency drop in the system is always higher than the protection threshold at the lowest frequency point. When the frequency deviation exceeds the set range, the active power output will be increased to curb the continued frequency drop and prevent the underfrequency load shedding protection function from being activated. Therefore: In the formula, Let t be the system frequency during time period t; This is the point of lowest frequency in the power system. The minimum inertia level under the frequency constraint at this lowest point is the corresponding system inertia. .

[0025] b. Minimum inertia requirement under the constraint of rate of change of frequency When the system faces unbalanced power When the system's frequency changes, the rate of change can be expressed as: In the formula, The system's rated frequency; This represents the upper limit of the system's rate of change.

[0026] The minimum inertia required by the system under the frequency change rate constraint for: Considering the constraints of the minimum frequency point and the rate of frequency change, the maximum value of the two is taken as the final basis for determining the minimum inertia required by the system: In the formula, This represents the minimum inertia requirement of the system.

[0027] Step 2: For the internal resource units of new market entities, based on the power margin, dynamic response characteristics of the resource units, and the continuous support capability for energy storage resource units, calculate the virtual inertia supply capability of each resource unit and each entity. The virtual inertia supply capacity of a resource unit in a given time period depends not only on its inertia control parameters but also on whether there is sufficient power margin during that time period. Considering wind power unit (wind), photovoltaic unit (PV), and energy storage unit (ess), the upper limit of virtual inertia that resource unit x can provide in time period t is: In the formula, Let x be the equivalent inertial time constant of resource unit x; This represents the power margin available for the inertial response during time period t.

[0028] Virtual inertia differs from the inherent rotational inertia of a synchronous machine. Its response process depends on the control links, including frequency measurement, filtering, control calculations, and converter execution. Therefore, in practical implementations, it typically exhibits a certain response delay and may be affected by factors such as current limiting, clipping, and differences in control modes. Considering the equivalent response delay of the frequency measurement-filtering-control link and the constraints of converter current limiting and clipping, a dynamic effectiveness coefficient for resource unit x is defined. for: In the formula, The effective duration of inertia; The equivalent delay time for the inertia response of resource unit x; The rate limiting or clipping reduction factor for resource unit x; This is the control mode reduction factor for resource unit x. All of the above parameters can be determined by type testing, grid connection certification, or historical disturbance data, and given as input parameters.

[0029] The maximum virtual inertia that resource unit x can provide during time period t. Represented as: a. Calculation of Virtual Inertia Supply Capacity of Wind Power Resources Let the predicted output of wind power resources in time period t be... The plan is to contribute to To provide inertia support in the early stages of disturbances, wind power resources need to reserve a certain amount of output adjustment margin in the operation plan; therefore, their power support margin is important. for: When the number of wind turbine units won in the electricity market is close to the predicted output, the additional power available for inertial response is limited, and the inertial supply capacity is reduced accordingly. When the predicted output is significantly higher than the number of units won in the electricity market, it indicates that there is a better inertial support capacity during that period.

[0030] The maximum virtual inertia that wind power resources can provide during time period t. for: In the formula, is the equivalent inertial time constant of wind power resources.

[0031] b. Calculation of Virtual Inertia Supply Capacity of Photovoltaic Resources The inertia supply capacity of photovoltaic resources is also primarily determined by the power margin available for initial disturbance support. Let the predicted power output of photovoltaic resources in time period t be... The plan is to contribute to To provide inertia support in the early stages of disturbances, photovoltaic resources need to reserve a certain amount of adjustable output capacity in their operation plans; therefore, their power support margin is crucial. for: The upper limit of virtual inertia that photovoltaic resources can provide in time period t for: In the formula, is the equivalent inertial time constant of photovoltaic resources.

[0032] c. Calculation of Virtual Inertia Supply Capacity of Energy Storage Resources Unlike wind and solar power, energy storage resources, when providing virtual inertia services, are constrained not only by power margin requirements but also by energy state. Even if an energy storage resource has a large discharge capacity at a certain moment, if its state of charge is insufficient or the available energy cannot cover the support needs during the effective duration of the inertia, its theoretical power margin cannot be fully converted into actual inertia supply capacity. Therefore, a persistence coefficient is further introduced when calculating the virtual inertia supply capacity of energy storage resources to characterize its inertia support capacity during the duration of the inertia response.

[0033] Assume the maximum discharge power of the energy storage resource is The planned discharge amount during time period t is Then its power support margin for: Energy storage resources are the effective available energy for inertial response. for: In the formula, The discharge efficiency of energy storage resources; The state of charge of the energy storage resource at time t; This represents the lower limit of the state of charge allowed by energy storage resources; This refers to the rated capacity of the energy storage resource.

[0034] Define the sustainability coefficient of energy storage resources for: when At this point, the available energy from the energy storage resources is sufficient to cover the energy required for the duration of the inertial response, and the sustainability coefficient is [value missing]. When available energy is insufficient, the sustainability coefficient decreases proportionally, thereby reducing and correcting the energy storage inertia supply capacity.

[0035] The maximum virtual inertia that energy storage resources can provide during time period t. for: In the formula, The equivalent inertial time constant of the energy storage resource.

[0036] Step 3: Determine the unit inertia cost of each resource unit based on the inertia function modification cost, single response operation cost, and energy reservation coefficient, and determine the lower limit of the inertia declaration price and the inertia declaration price for each entity to participate in the configuration based on the unit inertia cost. New market players participating in the inertia ancillary services market adopt a cost-based pricing method, which mainly includes modification costs and operating costs. Modification costs primarily reflect the investment in controller upgrades, power conversion equipment modifications, parameter tuning, testing and certification, and maintenance required for each player to integrate inertia control functions. Operating costs primarily reflect the additional losses, additional control actions, and equipment maintenance expenses incurred by each player during inertia response and recovery. Furthermore, considering that new market players typically need to reserve a certain power or energy margin when providing inertia services, thereby crowding out their available capacity for participating in the electricity market and resulting in potential revenue losses, an energy reservation coefficient is further introduced to adjust the base cost price, reflecting the upward effect of reservation behavior on the price of resource inertia services.

[0037] Inertia service quote for source unit x during time period t It can be uniformly represented as: In the formula, Cost per unit of inertia; For energy reserve factors, there are usually .

[0038] a. Bidding prices for wind power resources participating in the inertia ancillary services market Wind power resources provide inertia support primarily through methods such as additional virtual inertia control, rotor kinetic energy release, and rapid active power adjustment. The retrofit cost for inertia services mainly includes upgrading the wind turbine controller, embedding additional frequency response modules, parameter identification and tuning, grid connection testing, and investment in related monitoring and communication equipment. This defines the retrofit cost corresponding to a single inertia response of wind power resources. for: In the formula, Total investment for retrofitting the inertia function of wind power resources; The recovery factor for investment in wind power resource retrofitting; The annual equivalent service duration for wind power resources; This represents the average number of inertial response cycles per year for wind power resources.

[0039] Among them, the recovery coefficient Related to annual interest rate and annual equivalent service duration: In the formula, r is the annual interest rate.

[0040] The operating cost of inertia services for wind power resources is mainly reflected in the increased additional control actions, rising mechanical and electrical stresses, and corresponding increases in operation and maintenance expenses during inertia response and speed recovery. Considering that this cost primarily depends on whether the virtual inertia control function is operational, the operating cost generated by a single inertia response of wind power resources is denoted as... .

[0041] The maximum inertia that wind power resources can provide in a single inertial response for: In the formula, The average predicted output of wind power resources.

[0042] Wind power resource unit inertia base cost It can be represented as: By introducing an energy reservation coefficient The basic cost quote has been revised to include the inertia service quote for wind power resources. It can be represented as: b. Bidding prices for photovoltaic resources participating in the inertia ancillary services market Photovoltaic resources themselves do not possess synchronously rotating components. Their inertia support capability is mainly achieved through inverter-added control, rapid active power regulation, and necessary power margin reserves. The cost of retrofitting for inertia services primarily includes investments in inverter control strategy expansion, virtual inertia function module integration, control parameter tuning, frequency measurement and communication device configuration, and grid connection testing and certification. The retrofitting cost corresponding to a single inertia response of photovoltaic resources is... The definition is the same as that of wind power resources, namely: In the formula, Total investment for retrofitting the inertia function of photovoltaic resources; The recovery factor for investment in photovoltaic resource retrofitting; The annual equivalent service duration of photovoltaic resources; This represents the average number of inertial response cycles per year for photovoltaic resources.

[0043] The operating cost of photovoltaic (PV) resource inertia services mainly consists of additional control inputs to the inverter, additional equipment losses, and additional operation and maintenance expenses. Considering that this cost is also primarily related to whether the control function is activated, the operating cost of a single PV resource inertia response is denoted as... .

[0044] The maximum inertia that photovoltaic resources can provide in a single inertial response for: In the formula, It contributes to the average forecast of photovoltaic resources.

[0045] The basic cost per unit inertia of photovoltaic resources It can be represented as: By introducing an energy reservation coefficient The basic cost quotation has been revised, and the inertia service quotation for photovoltaic resources has been revised accordingly. It can be represented as: c. Pricing of energy storage resources in the inertia auxiliary services market Compared to wind and solar power, the inertial response of energy storage resources not only relies on additional control strategies but also requires actual energy release or absorption by the batteries. The retrofit cost for inertial services mainly includes investments in embedding virtual inertial control modules, upgrading the converter control system, expanding measurement and communication functions, parameter tuning, and grid connection testing and certification. The retrofit cost for a single inertial response of energy storage resources... The definition is the same as that of wind power and photovoltaic resources, namely: In the formula, Total investment for retrofitting the inertia function of energy storage resources; The recovery factor for investment in energy storage resource retrofitting; The annual equivalent service duration of energy storage resources; This represents the average number of inertial response cycles per year for energy storage resources.

[0046] The operating cost of inertial services for energy storage resources mainly comes from the additional charging and discharging losses of batteries during inertial response and recovery, accelerated cycle aging, and increased inverter operating losses. During the inertial response process, the energy storage resource system typically undergoes a short charging and discharging process. Although this process may not constitute a complete charging and discharging cycle, it still causes a certain degree of loss to battery life.

[0047] Energy released by a single inertial response of energy storage resources It can be represented as: In the formula, This is the moment of lowest frequency. This represents the maximum allowable frequency deviation of the system.

[0048] The equivalent number of cycles for a single inertial response of energy storage resources It can be represented as: In the formula, DoD represents the total energy generated over the entire lifespan of the energy storage resource; DoD represents the depth of charge and discharge of the battery inside the energy storage resource. The charging and discharging efficiency of the internal batteries of energy storage resources; This refers to the number of charge-discharge cycles throughout the entire lifespan of the energy storage resource.

[0049] The operating cost generated by this inertial response for: In the formula, This is the initial investment for energy storage resources.

[0050] The maximum inertia that energy storage resources can provide in a single inertial response for: Basic cost per unit inertia of energy storage resources It can be represented as: By introducing an energy reservation coefficient The base cost quote has been revised to include the inertia service quote for energy storage resources. It can be represented as: After obtaining inertia service quotations from basic resource units such as wind power, photovoltaics, and energy storage, an inertia pricing strategy at the entity level can be further formulated. Considering that new market entities such as independent energy storage power stations, new energy distribution and storage consortia, and power-type virtual power plants are essentially composed of multiple heterogeneous resource units, to ensure the overall revenue level of each entity in providing inertia services, each entity adopts an internal resource unit quotation upward aggregation strategy. That is, the highest quotation among all eligible inertia support resource units within the entity is used as the lower limit of the entity's inertia market bid price for the corresponding time period. Step 4: Establish an inertia auxiliary service market clearing model. Based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price, and inertia bid price, solve the model to obtain the inertia winning bid volume of each entity and determine the market clearing price. The model for new market entities participating in the inertia assisted services market is a two-layer model. In the upper layer model, each new market entity calculates its maximum available inertia and its inertia service bid based on the virtual inertia supply capacity calculation method and bidding strategy proposed in steps 2 and 3, and participates in the inertia assisted services market application to maximize its own inertia service revenue. Its objective function is as follows: set up This refers to the collective of entities participating in the inertia market, including independent energy storage power stations, new energy distribution and storage consortia, and power-generating virtual power plants. The main entities... The objective of maximizing market returns based on inertia can be expressed as: In the formula, The clearing price of the inertia market during time period t; as the main body The scalar value of inertia in time period t; as the main body The unit inertia base cost.

[0051] The following constraints must also be met: a. Inertia declaration quantity constraint main body Inertia declaration It should not exceed the upper limit of the virtual inertia it can provide: In the formula, as the main body The upper limit of virtual inertia that can be provided during time period t.

[0052] b. Inertia declaration price constraint main body Inertia declaration price The bid price should not be lower than the lower limit of the inertia bid calculated in step 3. Meanwhile, to prevent excessively high bid prices in the market, the system sets a uniform upper limit on the bid prices for all participants in the inertia ancillary services market. : In the formula, as the main body Participate in the lower limit of the inertia market price.

[0053] The lower-level model determines the winning bids for inertia from each entity with the objective of minimizing the system's inertia procurement cost, and further derives a unified market-clearing price for inertia from the dual variables of the system's frequency security constraints. Its objective function is: In the formula, as the main body The declared price for inertia services.

[0054] The following constraints must also be met: a. System minimum inertia requirement constraint Considering the time delay in the virtual inertia provided by new market players, at the initial moment of the disturbance, RoCoF is only related to the system disturbance loss power and the synchronous machine inertia level: In the formula, This represents the actual RoCoF value after the system is disturbed. Let be the unbalanced power at time t; This is the inertia of the system's synchronous machine.

[0055] System minimum inertia requirements for: At this time, the system has insufficient inertia. for: During the unified clearing process of the inertia auxiliary services market, the sum of the inertia bids won by all new market players should meet the system inertia deficit: b. Inertia scalar constraint The winning inertia of each entity should be less than its declared inertia: The process of solving the two-layer model to obtain the inertia bid-ask values ​​of each entity and determine the market clearing price includes: The process of solving the two-layer model to obtain the inertia bid-ask values ​​of each entity and determine the market clearing price includes: (1) The virtual inertia supply capacity obtained in step 2, the lower limit of the inertia declaration price and the inertia declaration price obtained in step 3, and the minimum inertia demand of the system obtained in step 1 are used as inputs to the two-layer model; (2) The inertia declaration amount and inertia declaration price of each subject in each time period are determined by the upper-level subject inertia market revenue maximization model, and the declaration results are used as input parameters of the lower-level market clearing model; (3) In the lower-level model, with the goal of minimizing the system inertia procurement cost, a unified clearing is carried out by combining the system inertia shortage constraint, the application quantity boundary constraint and the price boundary constraint to obtain the inertia winning bid quantity of each entity in each time period; (4) Transform the original feasibility conditions, dual feasibility conditions, first-order optimal conditions and complementary relaxation conditions of the lower-level market clearing model into the constraints of the upper-level model, and transform the bi-level model into a single-level optimization problem based on the KKT conditions. (5) The single-layer optimization problem is solved by a mathematical programming solver to obtain the optimal inertia target value of each subject in each time period; and the dual variable corresponding to the system inertia deficit constraint or unified clearing balance constraint is used as the market clearing price, thereby outputting the market clearing price of inertia auxiliary services in each time period.

[0056] Step 5: Generate an inertia auxiliary service call execution plan for the power system in the corresponding time period based on the inertia scalar values ​​of each subject, so as to provide physical support that meets frequency security constraints when the power system faces unbalanced power disturbances.

[0057] The process of generating the execution plan includes: determining the subject-level inertia call instructions according to the inertia benchmark of each subject in the corresponding time period; further decomposing the subject-level inertia call instructions into resource unit-level active power support instructions according to the unit inertia cost of internal resources from low to high and the response speed from fast to slow; for wind power and photovoltaic resources, issuing additional active power generation instructions to the corresponding current generator control unit; for energy storage resources, issuing fast discharge power instructions and simultaneously verifying their upper and lower limits of state of charge and maximum discharge power constraints.

[0058] Based on the minimum inertia requirement model in step 1, calculate the inertia requirement corresponding to each time period under the constraints of frequency change rate and frequency minimum point, and take the maximum value of the two as the minimum inertia requirement of the system. Based on the virtual inertia supply capacity calculation method in step 2, and combined with the power margin, dynamic effectiveness coefficient and energy storage sustainability coefficient of wind power, photovoltaic and energy storage in each time period, the virtual inertia supply capacity of each resource unit and each entity is calculated. Based on the pricing model in step 3, calculate the unit inertia cost, inertia bid price, and lower limit of inertia bid price for each resource unit. Substitute the system's minimum inertia requirement, the virtual inertia supply capacity of each entity, and the inertia declaration parameters into the two-layer market clearing model to obtain the inertia winning bid and market clearing price for each entity. The call execution plan is generated based on the obtained inertia scalar, and the frequency response process under the disturbance scenario is verified to verify the physical executability of the method of the present invention under frequency security constraints.

[0059] When a load change disturbance actually occurs in the power grid, the execution plan triggers the corresponding resource unit to output additional active power within the effective duration of inertia, thereby limiting the system frequency change rate and slowing down the frequency drop process. Subsequently, under the action of primary frequency regulation and subsequent power recovery, the system frequency transitions from a rapid drop process after the disturbance to a smooth recovery process, thereby achieving a smooth transition of the frequency curve and reducing the risk of triggering low-frequency load shedding protection.

[0060] Example 2 In this embodiment, the configuration method proposed in Embodiment 1 is simulated, wherein the system inertia is jointly provided by the thermal power unit, the independent energy storage power station, the new energy distribution and storage consortium, and the power source virtual power plant. The parameters of the thermal power unit and the independent energy storage power station are shown in Tables 1 and 2.

[0061] Table 1 Parameter Settings for Thermal Power Units Table 2 Parameter Settings for Independent Energy Storage Power Stations Both thermal power units have an inertial time constant of 6s. Given that thermal power units are usually operated continuously as a normally open power source in actual operation, their inherent synchronous inertia naturally assumes the function of supporting the system's basic inertia. Therefore, thermal power units are considered obligated inertia providers and are not included in the scope of declaration and clearing in the inertia ancillary services market.

[0062] The total system load is composed of the electricity demand of various demand-side entities and the system's rigid load. The maximum power disturbance during each period is 8% of the total load. The system's rated frequency is 50Hz, the upper limit of the allowable frequency variation rate is 0.5Hz, and the lowest frequency point is 49.5Hz. The total system load curve, the actual output and power margin of each participating entity in the ancillary services market in the electricity market are shown below. Figure 2 As shown. The unified price ceiling for inertia pricing across all entities is 4 yuan / MWs. The simulation process includes: In this embodiment, to facilitate the reproduction of the experiment by those skilled in the art, the effective duration T of the inertia is uniformly taken. I The time is 4 seconds; the relevant parameters for the dynamic effectiveness coefficients of wind power, photovoltaic power, and energy storage are respectively taken as follows: The inertia market clearing prices and the winning bids for each participant for the 96 time periods on this typical day are as follows: Figure 3 As shown.

[0063] Depend on Figure 3It can be seen that the clearing price of the system inertia market is generally within the range of 0 to 3.98 yuan / MWs, with an average clearing price of 1.82 yuan / MWs. Specifically, during periods when the system synchronization inertia is sufficient to meet frequency security requirements, the inertia shortage is zero, and no additional procurement is needed in the inertia market, resulting in a clearing price of 0. However, during periods of significant system inertia shortage, the inertia market price rises significantly, indicating that the inertia service price can effectively reflect changes in the system's dynamic frequency security requirements.

[0064] From the perspective of system inertia demand, there is an inertia deficit in 64 out of the 96 time periods throughout the day, requiring the procurement of virtual inertia from new market entities through the inertia auxiliary services market. In this typical daily scenario, although thermal power units can provide a certain amount of basic synchronous inertia, there is still a significant inertia deficit during periods of high load and large disturbance power. The virtual inertia provided by new market entities plays a crucial role in compensating for the system inertia deficit and improving system frequency stability.

[0065] From the perspective of meeting the system inertia deficit, there were only three periods throughout the day where a small amount of inertia was not fully met, with a total inertia deficit of 40.84 MWs. The vast majority of periods with inertia demand could be effectively supplemented through market-based allocation, indicating that the inertia auxiliary service market trading mechanism proposed in this invention can better coordinate the relationship between system inertia demand and the inertia supply of new market entities, and achieve effective allocation of inertia resources.

[0066] In this embodiment, the revenue of various new market entities participating in the inertia assisted services market on this typical day is further statistically analyzed, such as... Figure 4 As shown.

[0067] Depend on Figure 4 It is evident that the revenue structure of different new market players in the inertia ancillary services market varies significantly. Due to differences in resource composition, unit inertia cost, and available inertia capacity among the three types of players, their market settlement amounts, cost structures, and net profit levels also exhibit marked differences. The inertia market cost of aggregated players is not simply determined by the unified cost of the players, but is closely related to the order of call for heterogeneous resources within the entity; therefore, it is necessary to analyze the cost structure of each player in conjunction with the overall cost structure.

[0068] For independent energy storage power stations, the inertia service cost consists entirely of the energy storage resources, resulting in a relatively simple cost structure. Figure 4It can be seen that the market settlement amount for an independent energy storage power station is 0.31 million yuan, the energy storage cost is 0.12 million yuan, and the final net profit is 0.19 million yuan. Since an independent energy storage power station contains only a single energy storage resource, its inertia support cost does not involve the allocation between heterogeneous resources within the station. Market revenue mainly depends on the winning bid inertia scale of the energy storage resource and the unit inertia cost level. Energy storage resources, relying on a high equivalent inertia time constant and fast dynamic response capability, possess certain market value in the inertia ancillary services market.

[0069] For new energy power distribution and storage consortia, the cost is comprised of three types of resources: wind power, energy storage, and photovoltaic power. Figure 4 It is known that the market settlement amount of the new energy distribution and storage consortium is 0.73 million yuan, the total cost is 0.31 million yuan, and the final net profit is 0.42 million yuan. The inertia response cost of the new energy distribution and storage consortium mainly consists of wind power cost and photovoltaic cost, with energy storage cost accounting for a relatively small proportion. This indicates that after winning the bid, the inertia support is not shared equally among various internal resources, but rather allocated sequentially according to the unit inertia base cost from low to high. Combined with the cost calculation results, it can be seen that the unit inertia base cost of wind power resources within the new energy distribution and storage consortium is the lowest, followed by energy storage, and then photovoltaic. Therefore, after the main entity wins the bid, wind power resources first undertake the inertia support task; when the available inertia from wind power resources is insufficient, energy storage resources are then further utilized; while photovoltaic resources mainly play a supplementary support role when low-cost resources are insufficient. This result shows that although the new energy distribution and storage consortium has the advantage of synergistic support from wind, solar, and storage, its overall profitability is still constrained by high-cost internal resources.

[0070] For power-generating virtual power plants, the cost mainly consists of wind power and solar power. Figure 4 It is known that the market settlement amount of the power source type virtual power plant is 16,600 yuan, the total cost is 5,100 yuan, and the final net profit is 11,500 yuan, which is the highest among the three types of entities. Looking at the cost composition, its cost is almost entirely composed of wind power costs, with photovoltaic costs accounting for a very small proportion. This indicates that the power source type virtual power plant mainly relies on its internal wind power resources to undertake inertia support tasks in the inertia market. Combined with the cost calculation results, it can be seen that the unit inertia base cost of the internal wind power resources of the power source type virtual power plant is lower than that of photovoltaic resources. Therefore, after the entity wins the bid, wind power resources are given priority to undertake inertia support, and photovoltaic resources are only used to supplement when wind power resources are insufficient. Due to its high proportion of internal wind power resources and large power margin in most periods, the power source type virtual power plant can not only provide a large scale of virtual inertia, but also effectively reduce the overall inertia service cost by prioritizing the use of low-cost resources, thus demonstrating strong market competitiveness.

[0071] A review of the revenue composition of the three types of entities reveals that the revenue level of new market entities in the inertia auxiliary service market is not only related to the scale of inertia won in bids, but also closely related to their internal resource cost structure and the order of resource allocation. For aggregation entities, the higher the proportion of low-cost internal resources and the larger the scale of inertia they can allocate, the stronger their overall bidding competitiveness, and the higher their market winning volume and net revenue.

[0072] Example 3 In this embodiment, an inertia-assisted service configuration system considering the participation of new market entities is proposed, including: Demand estimation module: Constructs a minimum inertia demand model for the power system to obtain the minimum inertia demand for the power system at different time periods; Supply capacity calculation module: For the internal resource units of new market entities, based on the power margin, dynamic response characteristics of the resource units, and the continuous support capacity for energy storage resource units, the module calculates the virtual inertia supply capacity of each resource unit and each entity. Price determination module: Based on the inertia function modification cost, single response operation cost and energy reservation coefficient of each resource unit, the unit inertia cost of the resource unit is determined, and based on the unit inertia cost, the lower limit of the inertia declaration price and the inertia declaration price of each subject participating in the configuration are determined. Market Clearing Module: Establish an inertia auxiliary service market clearing model, and solve it based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price and inertia bid price to obtain the inertia winning bid quantity of each entity and determine the market clearing price. Execution plan generation module: Generates the inertia auxiliary service call execution plan of the power system in the corresponding time period based on the inertia standard of each subject, so as to provide physical support that meets frequency security constraints when the power system faces unbalanced power disturbances.

[0073] The methods of the present invention can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD-ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code originally stored on a remote recording medium or a non-transitory machine-readable medium and subsequently stored on a local recording medium, downloaded via a network. Thus, the methods described herein can be processed by software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components (e.g., RAM, ROM, flash memory, etc.) capable of storing or receiving software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the methods described herein. Furthermore, when a general-purpose computer accesses the code used to implement the methods shown herein, the execution of the code transforms the general-purpose computer into a dedicated computer for performing the methods shown herein.

[0074] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for configuring inertia-assisted services that considers the participation of new market entities, characterized in that, Includes the following steps: Construct a minimum inertia demand model for the power system to obtain the minimum inertia demand for the power system at different time periods; For internal resource units targeting new market entities, the virtual inertia supply capacity of each resource unit and each entity is calculated based on the power margin, dynamic response characteristics, and continuous support capacity of the energy storage resource unit. Based on the inertia function modification cost, single response operation cost and energy reservation coefficient of each resource unit, the unit inertia cost of the resource unit is determined, and based on the unit inertia cost, the lower limit of the inertia declaration price and the inertia declaration price for each subject to participate in the configuration are determined. A market clearing model for inertia auxiliary services is established. Based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price, and inertia bid price, the model is solved to obtain the inertia winning bid volume of each entity and determine the market clearing price. Based on the inertia scalar values ​​of each entity, an inertia auxiliary service call execution plan for the power system in the corresponding time period is generated.

2. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 1, characterized in that, The process of obtaining the minimum inertia requirements of the power system at different time periods includes: Calculate the minimum inertia requirement under the constraint of the lowest frequency point to prevent triggering low-frequency load shedding protection, under the operating condition where the power system inertia level remains constant. Calculate the minimum inertia requirement under the frequency change rate constraint based on the rated frequency of the power system, the upper limit of the frequency change rate of the power system, and the unbalanced power faced by the power system. The maximum value of the minimum inertia requirement under the constraint of the lowest frequency point and the minimum inertia requirement under the constraint of the frequency change rate is taken as the minimum inertia requirement of the power system for each time period.

3. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 1, characterized in that, When calculating the virtual inertia supply capacity based on the aforementioned dynamic response characteristics, the dynamic effectiveness coefficient of the resource unit is calculated using the following formula. : In the formula, The effective duration of inertia; The equivalent delay time for the inertia response of resource unit x; The rate limiting or clipping reduction factor for resource unit x; The control mode reduction factor for resource unit x.

4. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 3, characterized in that, When the internal resource units of new market entities include energy storage resources, the process of calculating virtual inertia supply capacity includes: The difference between the maximum discharge power of the energy storage resource and the planned discharge amount for the corresponding time period is used as the power margin of the energy storage resource. Based on the discharge efficiency, current state of charge, allowable state of charge limit, and rated capacity of the energy storage resources, calculate the effective available energy of the energy storage resources for inertial response. Determine whether the effective available energy is greater than or equal to the product of the power margin and the effective duration of inertia. If yes, the sustainability coefficient is set to 1. If no, the ratio of the effective available energy to the product is used as the sustainability coefficient characterizing the continuous support capability. The virtual inertia supply capacity of the energy storage resource is obtained by multiplying its equivalent inertia time constant, persistence coefficient, power margin, and dynamic effectiveness coefficient.

5. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 3, characterized in that, When the internal resource units of a new market entity include wind power or photovoltaic resources, the process of calculating the virtual inertia supply capacity includes: Obtain the predicted and planned power output values ​​of wind power or photovoltaic resources for the corresponding time period, and use the difference between the predicted and planned power output values ​​as the power support margin. The virtual inertia supply capacity of wind power or photovoltaic resources is obtained by multiplying the equivalent inertia time constant of the wind power or photovoltaic resources, the power support margin, and the dynamic effectiveness coefficient.

6. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 1, characterized in that, When the internal resource unit includes energy storage resources, the process for determining the single-response operation cost includes: Based on the maximum allowable frequency deviation of the power system, the rated frequency of the power system, and the maximum discharge power of the energy storage resources, calculate the energy released in a single inertial response; Using the total energy generated over the entire lifespan of the energy storage resource, the depth of charge and discharge of the internal battery, the charge and discharge efficiency, and the number of charge and discharge cycles over the entire lifespan, the released energy is converted into the equivalent number of cycles for a single inertial response. The ratio of the equivalent number of cycles to the number of charge-discharge cycles is multiplied by the initial investment in the energy storage resource to obtain the single-response operating cost of the energy storage resource.

7. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 1, characterized in that, The process of determining the lower limit of the inertia declaration price and the inertia declaration price for each participating entity includes: For a new market entity composed of multiple heterogeneous resource units, extract the bids of each resource unit within the entity that can participate in inertia support; An internal resource unit price aggregation strategy is adopted, and the highest price among the extracted resource unit prices is used as the lower limit of the inertia bid price for the entity in the corresponding time period.

8. The inertia auxiliary service configuration method considering the participation of new market entities according to claim 1, characterized in that, The market clearing model is a two-layer model that considers independent energy storage power stations (ES), new energy distribution and storage consortia (RES), and virtual power plants (DG). The upper-level model uses the maximization of the inertia market returns of each new market entity at the upper level as its objective function: In the formula, T represents the total number of time periods within the scheduling cycle. Trading hours For the group of participants in the inertia market, The total inertia revenue for participants in the inertia market during the scheduling cycle. The clearing price of the inertia market during time period t; as the main body The scalar value of inertia in time period t; as the main body The basic cost per unit of inertia; The lower-level model uses the minimum total cost of power system inertia procurement as its objective function: In the formula, as the main body Inertia service application price This represents the total cost of inertia procurement.

9. An inertia-assisted service configuration system considering the participation of new market entities, comprising the method described in any one of claims 1-8, characterized in that, include: Demand estimation module: Constructs a minimum inertia demand model for the power system to obtain the minimum inertia demand for the power system at different time periods; Supply capacity calculation module: For the internal resource units of new market entities, based on the power margin, dynamic response characteristics of the resource units, and the continuous support capacity for energy storage resource units, the module calculates the virtual inertia supply capacity of each resource unit and each entity. Price determination module: Based on the inertia function modification cost, single response operation cost and energy reservation coefficient of each resource unit, the unit inertia cost of the resource unit is determined, and based on the unit inertia cost, the lower limit of the inertia declaration price and the inertia declaration price of each subject participating in the configuration are determined. Market Clearing Module: Establish an inertia auxiliary service market clearing model, and solve it based on the minimum inertia demand, virtual inertia supply capacity, lower limit of inertia bid price and inertia bid price to obtain the inertia winning bid quantity of each entity and determine the market clearing price. Execution plan generation module: Generates the inertia auxiliary service call execution plan of the power system for the corresponding time period based on the inertia benchmark of each subject.

10. An electronic device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform an operation corresponding to the inertia-assisted service configuration method considering the participation of new market entities as described in any one of claims 1-8.

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