Climbing auxiliary service and electric energy combined clearing optimization method based on heterogeneous energy storage resource cooperation

Abstract

The invention discloses a heterogeneous energy storage cooperative climbing auxiliary service and electric energy combined clearing optimization method and system, and belongs to the field of electric power system operation and electric power markets. Aiming at the defects of homogeneous modeling, extensive climbing evaluation and the like in the prior art, an energy power station and a matched energy storage aggregation joint unit are innovated for the first time, a three-layer hierarchical collaborative response logic is constructed with a thermal power generating unit and independent energy storage, and a climbing demand is accurately matched according to differential response delay and function positioning. And constructing an integrated joint clearing model containing the system-level constraint and the main body exclusive refined climbing constraint, taking the minimum total cost of the whole period of the system as a target, solving by adopting a mixed integer linear programming algorithm, and outputting the clearing electric quantity, the climbing capacity and the price of each main body. According to the method, an independent climbing service market mechanism is set, the climbing capacity value is dominated, heterogeneous energy storage accurate cooperative compensation is achieved, the rapid climbing requirement of a high-proportion new energy system can be economically met, and the system operation safety and the new energy consumption level are improved.

Description

Technical Field

[0001] This invention belongs to the field of power system operation and power market technology. Specifically, it relates to a method and system for achieving coordinated optimization of power energy and ramp-up ancillary services, economic dispatch and precise compensation in a power system with a high proportion of renewable energy access, by treating thermal power units, independent energy storage systems and renewable energy-supporting energy storage joint units as differentiated market entities and through an integrated joint clearing model. Background Technology

[0002] With the advancement of the "dual carbon" target, the penetration rate of fluctuating renewable energy sources such as wind power and photovoltaics in the power system is rapidly increasing. The strong uncertainty, intermittency, and anti-peak-shaving characteristics of renewable energy output lead to drastic fluctuations in the net load curve of the power system, placing unprecedentedly high demands on the system's ability to rapidly increase and decrease power—that is, ramp-up flexibility. Traditional power dispatching and market models mainly focus on power balance and spinning reserve, lacking effective quantitative assessment, market-based pricing, and procurement mechanisms for rapid ramp-up capabilities at the minute or even second level, making it difficult to guarantee the safe, stable operation and efficient absorption of high-proportion renewable energy grids.

[0003] To address the challenge of insufficient system ramping capability, establishing a ramping assistance service market has become an industry consensus. However, existing technical solutions have significant limitations in design and implementation, restricting their practical effectiveness: Homogeneous Market Player Modeling: While most existing joint clearing methods propose a framework for energy storage participation in a joint market, they typically simplify or homogenize various flexible resources. In particular, they generally fail to model "new energy power plants and their associated energy storage systems" as a physically coupled, mutually beneficial, and collaborative whole. In reality, the primary goal of associated energy storage is to mitigate power output fluctuations at new energy power plants and reduce curtailment; its operational logic differs fundamentally from that of "independent energy storage power plants" as independent profit-making entities. Existing technologies ignore this difference, resulting in models that cannot accurately depict the true adjustment potential and costs of different energy storage resources, potentially leading to uneconomical or infeasible clearing outcomes.

[0004] The assessment of ramp-up capacity is often too broad: existing methods for modeling resource ramp-up capacity tend to focus on general power increase / decrease rate constraints, failing to consider the technical characteristics and boundaries of different resources in detail. For example, for thermal power units, their ramp-up capacity is limited by the physical ramp-up rate and the upper and lower limits of output; for energy storage, although its instantaneous ramp-up capacity is high, its sustainability heavily depends on its current state of charge; for a combination of renewable energy and energy storage, its ramp-up capacity is simultaneously constrained by the dual coupling of renewable energy prediction errors, real-time output, and energy storage status. This lack of differentiated and refined capacity modeling prevents the market from accurately identifying and purchasing the true and available ramp-up capacity of various resources, resulting in resource mismatch and efficiency losses.

[0005] Lack of coordination and compensation mechanisms: Due to the crude modeling, the existing market mechanism is unable to achieve optimal economic coordination among heterogeneous flexible resources such as thermal power, independent energy storage, and supporting energy storage when providing ramp-up services. It is impossible to design a clearing and pricing mechanism that can guide them to "play to their strengths and complement each other's advantages" based on their differences in response speed, regulation accuracy, duration, and operating costs, thus making it difficult to meet the system ramp-up needs at the lowest total social cost.

[0006] Therefore, an innovative joint clearing and optimization method is urgently needed to fundamentally solve the above problems. This method should achieve precise coordination and value compensation between heterogeneous energy storage resources and thermal power through refined and differentiated modeling of market players. It should also enable multi-player collaborative optimization to meet the system's flexible ramp-up requirements, reduce operating costs, and improve the absorption of new energy sources. Summary of the Invention

[0007] The purpose of this invention is to overcome the aforementioned deficiencies of existing technologies and provide a method and system for optimizing ramp-up ancillary services and joint energy clearing, incorporating different energy storage systems. The core of this method lies in: innovatively modeling a "new energy-supporting energy storage joint unit" as a unified market entity, and constructing a differentiated ramp-up capability assessment model and collaborative clearing mechanism. This allows for precise quantification and economical dispatching of the ramp-up value of heterogeneous resources such as thermal power, independent energy storage, and supporting energy storage within a unified market framework. Ultimately, this achieves the goal of minimizing total system cost to meet ramp-up flexibility requirements and significantly improves the level of new energy absorption and grid operation security.

[0008] The core innovations are as follows: The core innovation of this invention lies in breaking through the limitations of existing technologies such as "homogeneous modeling, extensive evaluation, and lack of collaborative mechanisms," resulting in three major substantial technical improvements, as follows: Innovation Point 1: Pioneering a unified modeling mechanism for "new energy supporting energy storage joint units". This mechanism aggregates new energy power plants and supporting energy storage systems into independent market entities, clearly defining their core objective of "fluctuation compensation ramp-up", which is fundamentally different from the "system-level rapid replacement" operation logic of independent energy storage, filling the gap in existing technologies that do not distinguish between the two types of energy storage resources.

[0009] Innovation Point 2: Establishing a "three-tiered, graded, and coordinated response" logic. Based on response delay and functional positioning, the system is tiered: thermal power units (response delay ≤ 5 minutes) provide basic ramp-up capacity, independent energy storage (response delay ≤ 1 minute) quickly fills the ramp-up gap, and new energy supporting energy storage joint units (response delay ≤ 30 seconds) precisely offset new energy fluctuations, achieving a precise match between ramp-up demand and resource capacity.

[0010] Innovation Point 3: Constructing a refined ramp-up constraint system. Dedicated constraints are designed for three types of entities: thermal power units combining start-stop status and ramp-up rate constraints; independent energy storage coupled with state of charge (SOC) and energy margin constraints; and supporting energy storage joint units linking new energy prediction deviations and energy storage status constraints, breaking through the limitations of existing technologies that only consider general power rates.

[0011] The specific technical solution is as follows: When constructing a joint market framework, new energy power plants and their supporting energy storage systems are aggregated into a new energy-supporting energy storage joint unit, which serves as a unified market entity, participating in market clearing alongside thermal power units and independent energy storage systems. This joint unit focuses on coordinated operation, achieving efficient absorption of wind and solar power curtailment on one hand, and providing the system with ramp-up and adjustment capabilities on the other. Its net output... The definition is as follows: ; in, For new energy power plants exist Actual output at any given moment; and Each is a supporting energy storage system exist The charging power and discharging power.

[0012] Clearly define the differentiated roles and capability boundaries of three types of entities in ramp-up services: independent energy storage, new energy supporting energy storage joint units, and thermal power units, and establish a hierarchical collaborative response logic.

[0013] Thermal power units are responsible for supplying basic ramp-up capacity, and a fixed ramp-up rate constraint is set based on minimum technical output and fuel cost characteristics; the ramp-up capacity constraint they provide is expressed as follows: ; ; In the formula, For the unit exist Constant effort and thermal power units Minimum and maximum output, Whether the unit is in the start-up or shutdown process at any given time; and thermal power units The uphill and downhill speeds, For time period, and The units exist The capacity of uphill and downhill climbing assistance services provided at all times; Independent energy storage undertakes the task of rapid response to ramp-up deficits, dynamically adjusting the ramp-up response threshold based on the state of charge (SOC) to avoid the risks of overcharging and over-discharging; its ramp-up capacity constraint is expressed as: ; ; In the formula: and Each is an independent energy storage system At any moment The charging power and discharging power; For independent energy storage systems Rated power; For independent energy storage systems At any moment The state of charge; For independent energy storage systems Rated capacity; and Each is an independent energy storage system The charging efficiency and discharging efficiency; For time period; and Each is an independent energy storage system The minimum and maximum states of charge; and Each is an independent energy storage system At any moment The capacity of the uphill and downhill climbing assistance services provided.

[0014] The integrated energy storage unit supporting new energy sources undertakes ramp-up services to compensate for fluctuations in new energy output. Its ramp-up capacity is positively correlated with the new energy forecast deviation coefficient, achieving precise offsetting of fluctuations. Its ramp-up capacity constraint is expressed as follows: ; ; in, For new energy power plants exist Predicting output at any given moment; For new energy power plants exist Actual output at any given moment; and Each is a supporting energy storage system exist The charging power and discharging power; To support the energy storage system Rated power; To support the energy storage system At any moment The state of charge; To support the energy storage system Rated capacity; and Each is a supporting energy storage system The charging efficiency and discharging efficiency; For time period; and Each is a supporting energy storage system The minimum and maximum states of charge; and These are combined energy storage units for new energy sources. exist The capacity of uphill and downhill assist services provided at all times.

[0015] Based on the above mechanism, an integrated joint clearing and optimization system is constructed, with the goal of minimizing the total cost throughout the system's lifecycle. This total cost encompasses the operating costs of thermal power units, the charging and discharging costs of independent energy storage, the collaborative operation costs of new energy supporting energy storage units, the cost of wind and solar curtailment penalties, and the cost of ramp-up capacity deficit penalties. The system ramp-up capacity deficit penalty cost is defined and included in the objective function as follows: This includes the unmet upward ramp-up capacity demand of the system, i.e., the upward ramp-up capacity deficit. Multiply by a preset upward ramp capacity price cap Simultaneously, the unmet downward ramp capacity demand of the system, i.e., the downward ramp capacity deficit, will be addressed. Multiplied by a preset downward ramp capacity price cap The upper limit of the ramp-up and ramp-down capacity price is the maximum cost per unit capacity that the system operator is willing to pay in order to cope with the risk of net load fluctuations.

[0016] The constraint system includes system-level constraints such as system power balance, reserve reserves, and ramping flexibility requirements, as well as dedicated physical constraints designed for the three types of entities. The core of these constraints is to provide capability constraints for differentiated ramping capacity, enabling precise matching of ramping capabilities of heterogeneous entities with system requirements.

[0017] The optimization system is solved by a mixed integer linear programming algorithm, which outputs the cleared power of each entity, the cleared ramp service capacity, the differentiated compensation amount, and the corresponding clearing price. Based on the clearing results, scheduling instructions are generated to guide the refined operation of each entity and ensure the system's ramping safety and economic efficiency.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention creates a value discovery and compensation mechanism for ramp-up assistance services. By establishing an independent ramp-up service cost item and ramp-up demand constraints, ramp-up capability is made explicit as a tradable commodity, establishing a market-based compensation mechanism of "whoever provides, benefits," opening up new revenue channels for rapidly adjustable resources such as energy storage, and effectively incentivizing flexible investment.

[0019] This invention achieves precise coordination of heterogeneous and flexible resources. Through refined modeling of differentiated ramp-up capabilities for thermal power, independent energy storage, and renewable energy-supported energy storage, it is the first to explicitly distinguish and model independent energy storage and renewable energy-supported energy storage within a clearing model, taking into account their differences in operational objectives and flexibility provision mechanisms. This makes the model more realistic. It enables the dispatch system to optimally combine and allocate resources in the energy market and ramp-up market based on their respective physical characteristics and economic viability.

[0020] This invention improves the economy and security of high-proportion renewable energy systems, and the joint optimization avoids suboptimal decisions that may result from individually optimizing energy and reserves. The system can meet ramp-up requirements at a lower overall cost, reducing reliance on deep peak shaving and frequent start-ups and shutdowns of thermal power units, thus lowering operating costs. Simultaneously, by pooling sufficient and high-quality ramp-up resources through market mechanisms, it significantly enhances the grid's robustness in responding to renewable energy fluctuations, ensuring power supply security and efficient renewable energy consumption. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the implementation steps of the method of the present invention. Figure 2 Forecast curves of load and new energy sources Figure 3 A joint analysis of the output bars of each generating unit. Figure 4 Figure 1 shows the state of charge (SOC) change curves for each energy storage system. Figure 5 Bar chart of charge and discharge power for each energy storage system Figure 6 Bar chart showing the allocation of market capacity among various market players during the ramp-up phase. Figure 7 Price curves for clearing the electricity market and the ramp-up ancillary services market Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. The illustrative embodiments and descriptions herein are used to explain the present invention, but are not intended to limit the present invention.

[0023] This embodiment provides a method for optimizing ramp-up assistance services and joint power clearing based on heterogeneous energy storage resource collaboration, such as... Figure 1 As shown, the specific steps are as follows: S1: Building a Joint Market Framework The market operator has identified the market participants involved in the joint clearing process, including conventional thermal power units, independent electrochemical energy storage power stations, and integrated units combining wind power / solar power and energy storage. The operator will collect system load forecast curves and forecast output curves for wind and solar power plants for the next 24 hours. Each market participant will submit its technical parameters to the market operator, such as the upper and lower limits of unit output, ramp rate, energy storage power and capacity, efficiency, etc., as well as its electricity price for each time period. The operator will also need to obtain information on its system ramp-up and ramp-up ancillary services requirements.

[0024] S2: Clarify the differentiated positioning and hierarchical collaboration logic of the three types of entities. The differentiated roles and capability boundaries of three types of entities in ramp-up services are clearly defined: independent energy storage, new energy-supporting energy storage joint units, and thermal power units. A hierarchical collaborative response logic is established: thermal power units are responsible for supplying basic ramp-up capacity with a response delay of ≤5 minutes, and a fixed ramp-up rate constraint is set based on minimum technical output and fuel cost characteristics; independent energy storage is responsible for quickly responding to ramp-up gaps with a response delay of ≤1 minute, and the ramp-up response threshold is dynamically adjusted based on the state of charge (SOC) to avoid the risks of overcharging and over-discharging; new energy-supporting energy storage joint units are responsible for ramp-up services that compensate for fluctuations in new energy output with a response delay of ≤30 seconds, and their ramp-up capacity provision capability is positively correlated with the new energy prediction deviation coefficient to achieve precise offsetting of fluctuations. S3: Establish an integrated joint clearing optimization model.

[0025] A unified clearing model encompassing electrical energy and ramp-up ancillary services is constructed. The objective function of this clearing model is to minimize the sum of the following costs under the predicted scenario: thermal power generation costs, start-up costs, shutdown costs, no-load costs, charging and discharging costs of independent energy storage systems, net output costs of new energy-supporting energy storage combined units, costs for ramp-up / ramp-up capacity deficits, and costs for wind and solar curtailment penalties. The objective function is obtained as follows: The expression is: ; In the formula, Total number of clearing periods; This represents the total number of thermal power units in the system. For the unit exist The price of electricity at any given moment; For the unit exist Efforts made at all times; and The units exist A quote for start-up and shutdown costs at any given time; For the unit exist No-load cost quotation at a certain moment; Indicates whether the unit is in the startup process at a certain moment; Indicates whether the unit is in the shutdown process at a certain moment; Is the total number of new energy supporting energy storage combined units; Is the combined unit Net output quotation; Is the new energy power station Penalty cost for wind and light curtailment; Is the total number of independent energy storage systems; And Are respectively the independent energy storage systems At the moment Discharge and charge power; And Are respectively the independent energy storage systems Discharge quotation and charge quotation; And Are respectively the upper limits of the upward and downward ramping capacity prices, reflecting the expected costs that the system is willing to pay for the load shedding / wind and light curtailment risks caused by the power imbalance due to the uncertainty of new energy power generation.

[0026] And establish a comprehensive set of constraint conditions, which mainly include system power balance constraints; upper and lower limits of thermal power unit output, minimum start-stop time, ramping rate constraints; charge and discharge power and state of charge constraints of energy storage systems; system reserve capacity constraints; system ramping flexibility capacity demand constraints; ramping deficit constraints; capacity constraints for each entity to provide ramping capacity. Among the above constraint conditions, System power balance constraint ; In the formula, Is the system Load demand at a certain moment.

[0027] (2) Reserve constraints provided by thermal power units ; ; In the formula, And Are respectively the positive reserve and negative reserve coefficients.

[0028] (3) Upper and lower limits of thermal power unit output constraints ; In the formula, And Are respectively the minimum output and maximum output of the thermal power unit (4) Thermal power unit operating state constraints ; In the formula, For thermal power units Initial running state (5) Minimum operating and shutdown time constraints for thermal power units ; In the formula, For thermal power units Minimum boot time; For thermal power units Minimum downtime.

[0029] (6) Climbing constraints of thermal power units ; In the formula, and thermal power units Uphill speed and downhill speed (7) Power system constraints on ramping demand of ramping auxiliary service system ; In the formula, and For each system There is a constant need for both uphill and downhill climbing.

[0030] (8) Shortage constraints of ramp-up products ; In the formula, and The system is respectively in There is a constant shortage of capacity when climbing uphill or downhill.

[0031] (9) Thermal power units provide ramping capacity constraints ; ; In the formula, and The units exist The capacity of uphill and downhill climbing assistance services provided at all times; (10) Charge and discharge constraints of independent energy storage systems ; ; In the formula, and Each is an independent energy storage system At any moment The charging power and discharging power; For independent energy storage systems Rated power; and The variables are 0-1, representing independent energy storage systems respectively. At any moment The charging state variables and discharging state variables; (11) State of charge constraints of independent energy storage systems ; ; In the formula, For independent energy storage systems At any moment The state of charge; For independent energy storage systems Rated capacity; and Each is an independent energy storage system The charging efficiency and discharging efficiency; For time period; and Each is an independent energy storage system The minimum and maximum states of charge.

[0032] (12) Independent energy storage systems provide ramp-up capacity constraints

[0033] ; ; In the formula, and Each is an independent energy storage system At any moment The capacity of the uphill and downhill climbing assistance services provided; (13) Power balance constraints within the new energy supporting energy storage unit

[0034] ; (14) Output constraints of new energy power plants ; In the formula, Energy storage integrated unit for new energy During the period Net effluent power; For new energy power plants exist Predicting output at any given moment; For new energy power plants exist Actual output at any given moment; (15) Supporting energy storage charging and discharging constraints ; ; In the formula, and Each is a supporting energy storage system exist The charging power and discharging power; To support the energy storage system Rated power; and The variables are 0 and 1, representing the supporting energy storage system, respectively. At any moment The charging state variables and discharging state variables; (16) Supporting energy storage state of charge constraints ; ; In the formula, To support the energy storage system At any moment The state of charge; To support the energy storage system Rated capacity; and Each is a supporting energy storage system The charging efficiency and discharging efficiency; For time period; and Each is a supporting energy storage system The minimum and maximum states of charge.

[0035] (17) New energy supporting energy storage unit provides ramp-up capacity constraint ; ; In the formula, and These are combined energy storage units for new energy sources. exist The capacity of uphill and downhill climbing assistance services provided at all times; S4: Solve the model and output the results.

[0036] The above optimization model is input into the commercial mathematical optimization solver GUROBI for integrated solution. Under the condition of satisfying all constraints, the solver seeks the decision variable values ​​that minimize the objective function, namely the power clearing and ramp-up capacity clearing results of each market participant in each time period.

[0037] The market operator releases the clearing results, including the planned power generation / charging / discharging power of each thermal power unit, independent energy storage, and new energy supporting energy storage unit for each time period in the next 24 hours; the purchased upward / downward ramp capacity; and the clearing prices for electricity and upward / downward ramp ancillary services. The electricity clearing price equals the shadow price of the system power balance constraint, and the upward / downward ramp ancillary service clearing price equals the shadow price of the system ramp demand constraint. Each market participant executes its operations according to the clearing plan, and the system dispatch center monitors and evaluates the process.

[0038] To verify the effectiveness of the method of this invention, simulation tests were conducted on an improved IEEE 30-node system. The system includes six thermal power units, two independent energy storage power stations with a total power of 30MW and a capacity of 60MWh, as well as one "wind power + energy storage" combined unit and one "photovoltaic + energy storage" combined unit, with a total wind power installed capacity of 40MW and a total energy storage capacity of 20MW and 40MWh. The dispatch cycle is 24 hours, and the time resolution is 15 minutes. The predicted output and load curves of new energy sources are shown below. Figure 2 The parameters of the thermal power units are shown in Table 1, and the energy storage parameters are shown in Table 2.

[0039] Table 1 Table 2 Based on the clearing results obtained from the simulation, the market operator issues operating plans for each time period within 24 hours to all market participants: thermal power units operate according to the predetermined output curve, such as... Figure 3 As shown, frequent start-stop cycles and deep peak shaving are avoided; independent energy storage and new energy-supported energy storage systems strictly implement charging and discharging power plans based on their own dynamic changes in state of charge, such as... Figure 4 and Figure 5 As shown in Figure 6, ramping services are provided according to the ramping capacity allocation results; the electricity market and the ramping ancillary services market settle fees according to the clearing price curve, as shown in Figure 6. Figure 7 As shown, the system dispatch center monitors the operational status of each entity in real time to ensure that all constraints are met and to guarantee the safe and stable operation of the power grid.

[0040] Three further scenarios were set up for comparison: Scenario 1: Only the traditional market clearing of electricity and ramp-up ancillary services is carried out, without introducing an energy storage model, and ramp-up services mainly rely on thermal power units.

[0041] Scenario 2: Energy storage participates in the joint clearing of the electricity and ramp-up auxiliary service market, but the energy storage is modeled in a homogeneous way and there is no hierarchical coordination mechanism.

[0042] Scenario 3: The method proposed in this invention, which combines hill-climbing assistance service and joint power clearing optimization based on heterogeneous energy storage resource synergy, integrates three types of resources: thermal power, independent energy storage, and new energy supporting energy storage.

[0043] Table 3 Table 3 compares the economic efficiency and operational indicators under the three scenarios. Scenario 1 adopts the traditional joint clearing method without introducing an energy storage model. The ramp-up service mainly relies on thermal power units. Due to their limited response speed (minutes) and technical output constraints, it is difficult to match the rapid ramp-up demand brought about by the fluctuation of new energy sources, resulting in both ramp-up deficit and regulation redundancy.

[0044] Scenario 2 employs existing technical solutions, which, while introducing energy storage to participate in joint clearing, fail to distinguish the core differences between independent energy storage and new energy-supporting energy storage: the former aims for "system-level rapid replenishment," while the latter's core mission is "fluctuation compensation." This homogeneous modeling results in the fluctuation offsetting advantage of supporting energy storage not being fully utilized, and the rapid response capability of independent energy storage being wasted. Ultimately, this leads to the dual problems of "high ramp-up deficit costs + high wind and solar curtailment costs," failing to fundamentally solve the challenge of coordinated scheduling of heterogeneous resources.

[0045] Scenario 3 applies the method proposed in this invention, integrating independent energy storage and renewable energy-supporting energy storage in joint clearing. The addition of these two types of energy storage significantly enhances the system's ramp-up adjustment capability through their complementary characteristics: on the one hand, the energy storage response speed can reach millisecond levels, accurately tracking rapid changes in load and renewable energy output, filling the "time lag" in traditional unit adjustments, and reducing the risk of ramp-up deficit; on the other hand, the large-scale capacity of independent energy storage can provide system-level ramp-up support, while supporting energy storage can smooth out fluctuations in renewable energy plant output and reduce local ramp-up demands. The synergy between the two enables the joint clearing model to more efficiently match the dual needs of "electricity supply - ramp-up adjustment." Results show that compared to Scenario 1, the total operating cost of this invention is reduced by RMB 1.1065 million, the renewable energy absorption rate is improved, wind and solar curtailment costs are significantly reduced, and ramp-up deficit costs are substantially decreased. Compared to Scenario 2, the total operating cost of this invention is reduced by RMB 652,700, the renewable energy absorption rate is increased by 2.43 percentage points, and ramp-up deficit costs are further reduced, verifying the significant effects of this invention's method in improving system economy, flexibility, and renewable energy absorption levels.

[0046] From the results of the clearing optimization, the flexible adjustment of the two types of energy storage significantly improves the system's natural ramping capability. The joint clearing model can more accurately allocate ramping capacity while meeting the balance of power supply and demand, reducing the redundant thermal power capacity reserved to ensure ramping safety, thereby improving the overall resource allocation efficiency.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing ramp-up assistance services and joint power clearing based on heterogeneous energy storage resource synergy, characterized in that, This is achieved by constructing and solving the following integrated joint clearing optimization model: A joint market framework will be established, which will aggregate new energy power plants and their supporting energy storage systems into a new energy supporting energy storage joint unit as a unified market entity, and participate in market clearing together with thermal power units and independent energy storage systems. The differentiated roles and capability boundaries of three types of entities in ramp-up services are clearly defined: independent energy storage, new energy-supporting energy storage joint units, and thermal power units. A hierarchical collaborative response logic is established: thermal power units are responsible for supplying basic ramp-up capacity with a response delay of ≤5 minutes, and a fixed ramp-up rate constraint is set based on minimum technical output and fuel cost characteristics; independent energy storage is responsible for quickly responding to ramp-up gaps with a response delay of ≤1 minute, and the ramp-up response threshold is dynamically adjusted based on the state of charge (SOC) to avoid the risks of overcharging and over-discharging; new energy-supporting energy storage joint units are responsible for ramp-up services that compensate for fluctuations in new energy output with a response delay of ≤30 seconds, and their ramp-up capacity provision capability is positively correlated with the new energy prediction deviation coefficient to achieve precise offsetting of fluctuations. Based on the above mechanism, an integrated joint clearing and optimization system is constructed with the goal of minimizing the total cost of the system throughout its entire life cycle. The total cost includes the operating cost of thermal power units, the charging and discharging cost of independent energy storage, the collaborative operation cost of new energy supporting energy storage joint units, the cost of wind and solar curtailment penalties, and the cost of ramping shortfall penalties. The constraint system includes system-level constraints such as system power balance, reserve reserves, and ramping flexibility requirements, as well as exclusive physical constraints designed for the three types of entities. The core of these constraints is to provide capability constraints for differentiated ramping capacity, so as to achieve precise matching between the ramping capacity of heterogeneous entities and system requirements. The optimization system is solved by a mixed integer linear programming algorithm, which outputs the cleared energy, ramp service capacity, and corresponding clearing price of each entity. Based on the clearing results, scheduling instructions are generated to guide the refined operation of each entity and ensure the system's ramping safety and economic efficiency.

2. The method for optimizing ramp-up assistance services and joint power clearing based on heterogeneous energy storage resource synergy according to claim 1, characterized in that, The aforementioned new energy supporting energy storage integrated unit consists of a new energy power plant and its supporting energy storage system, participating in the market as a unified entity, with its net power output... Represented as: ； in, For new energy power plants exist Actual output at any given moment; and Each is a supporting energy storage system exist The charging power and discharging power.

3. The method according to claim 1, characterized in that, The differentiated ramp capacity provides capacity constraints in the following aspects: For new energy supporting energy storage combined units, the upslope capacity they can provide is limited by the difference between the predicted upper limit of the new energy power station and the actual output, as well as the available discharge power of the supporting energy storage system based on the current state of charge; the downslope capacity they can provide is limited by the difference between the actual output of the new energy power station and the minimum technical output, as well as the available charging power of the supporting energy storage system based on the current state of charge. Its climbing capacity constraint is expressed as: ； ； in, For new energy power plants exist Predicting output at any given moment; For new energy power plants exist Actual output at any given moment; and Each is a supporting energy storage system exist The charging power and discharging power; To support energy storage systems Rated power; To support energy storage systems At any moment The state of charge; To support energy storage systems Rated capacity; and Each is a supporting energy storage system The charging efficiency and discharging efficiency; For time period; and Each is a supporting energy storage system The minimum and maximum states of charge; and These are combined energy storage units for new energy sources. exist The capacity of uphill and downhill assist services provided at all times.

4. The method according to claim 1, characterized in that, In the aforementioned differentiated ramp capacity provisioning constraints, for an independent energy storage system, its available ramp capacity is limited by the difference between its rated discharge power and the current discharge power, as well as the available energy margin based on the current state of charge and the minimum state of charge. Its climbing capacity constraint is expressed as: ； ； In the formula: and Each is an independent energy storage system At any moment The charging power and discharging power; For independent energy storage systems Rated power; For independent energy storage systems At any moment The state of charge; For independent energy storage systems Rated capacity; and Each is an independent energy storage system The charging efficiency and discharging efficiency; For time period; and Each is an independent energy storage system The minimum and maximum states of charge; and Each is an independent energy storage system At any moment The capacity of the uphill and downhill climbing assistance services provided.

5. The method according to claim 1, characterized in that, In the aforementioned differentiated ramp capacity provision constraint, for thermal power units, the upward ramp capacity they can provide is jointly determined by the unit's current output, maximum output, and upward ramp rate; the downward ramp capacity they can provide is jointly determined by the unit's current output, minimum technical output, and downward ramp rate. Its climbing capacity constraint is expressed as: ； ； In the formula, For the unit exist Constant effort and thermal power units Minimum and maximum output, Whether the unit is in the start-up or shutdown process at any given time; and thermal power units The uphill and downhill speeds, For time period, and The units exist The capacity of uphill and downhill assist services provided at all times.

6. The method according to claim 1, characterized in that, The system ramp-up capacity deficit penalty cost is defined and included in the objective function as follows: the unmet upward ramp-up capacity demand, i.e., the upward ramp-up capacity deficit, is calculated. Multiply by a preset upward ramp capacity price cap Simultaneously, the unmet downward ramp capacity demand of the system, i.e., the downward ramp capacity deficit, will be addressed. Multiplied by a preset downward ramp capacity price cap The upper limit of the ramp-up and ramp-down capacity price is the maximum cost per unit capacity that the system operator is willing to pay in order to cope with the risk of net load fluctuations.

7. A joint clearing system for the electricity market, characterized in that, include: The market entity modeling module is used to construct a set of market entities that includes thermal power units, independent energy storage systems, and new energy supporting energy storage joint units. The data acquisition module is used to obtain system load forecasts, new energy power output forecasts, technical parameters of market entities, and market quotations. An optimization modeling module is used to establish an integrated joint clearing optimization model as described in any one of claims 1 to 6; The solution module is used to solve the optimization model and output the clearing results of electrical energy and ramp capacity; The plan generation module is used to generate a power generation dispatch plan based on the clearing results and issue it for execution.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 7.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 7.

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