A photovoltaic park and shared energy storage collaborative optimization scheduling method for spot-climbing combined market

Abstract

The application discloses a photovoltaic park and shared energy storage collaborative optimization scheduling method for spot-climbing combined market, comprising: constructing an alliance operation framework composed of multiple photovoltaic parks and shared energy storage, and uniformly participating in day-ahead electricity market, natural gas market and climbing market transaction; a shared energy storage cycle aging model based on a cumulative attenuation function is established, and a nonlinear attenuation process is embedded into a day-ahead collaborative optimization model through piecewise linearization; a collaborative optimization scheduling model considering net cost of spot market transaction, gas purchase cost, operation and maintenance cost, demand response cost, shared energy storage cycle aging cost, step carbon trading cost and climbing income is constructed, and alliance electricity purchase and sale plan, gas purchase plan, equipment output, shared energy storage charging and discharging plan and climbing capacity declaration result are obtained; an improved Shapley cost allocation model is constructed based on total operation cost and carbon emission reduction contribution of the alliance, and an alliance distribution result considering economic contribution and environmental rights and interests is obtained. Experiments show that the method can significantly improve the operation economy, flexible adjustment capability and alliance stability of the photovoltaic park and the shared energy storage in the spot-climbing combined market.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system optimization scheduling and energy market collaborative trading technology, and in particular relates to a method for collaborative optimization scheduling of photovoltaic parks and shared energy storage for the spot-ramp joint market. Background Technology

[0002] Against the backdrop of the ongoing development of new power systems and energy markets, photovoltaic industrial parks are gradually evolving from single energy-consuming units to multi-energy coupled, market-oriented operating entities. Shared energy storage, with its capabilities of bidirectional power regulation, cross-time energy transfer, and flexible support for ancillary services, has become an important means for photovoltaic industrial parks to improve their renewable energy consumption levels, peak shaving and valley filling capabilities, and market revenue.

[0003] However, existing methods for coordinating the operation of photovoltaic industrial parks and shared energy storage mostly focus on a single electricity market or a single ancillary service scenario, rarely considering the joint optimization of day-ahead spot trading, natural gas procurement, and flexible ramp-up ancillary services. Furthermore, traditional dispatch methods often ignore the cyclic aging costs incurred by shared energy storage during frequent charging and discharging, easily leading to over-utilization of shared energy storage and causing optimization results to deviate from true economic efficiency. In addition, existing alliance allocation methods typically only allocate costs or benefits based on marginal economic contributions, failing to reasonably reflect the actual contributions of each entity to carbon emission reduction and low-carbon operation, thus affecting the long-term stability of the alliance. Summary of the Invention

[0004] Purpose of the Invention: To address the problems of insufficient grid absorption capacity of photovoltaic (PV) parks operating independently and the lack of a coordinated scheduling mechanism between the spot market and the ramp-up ancillary service market in existing technologies, this invention provides a method for the coordinated and optimized scheduling of PV parks and shared energy storage in a spot-ramp joint market. While ensuring the safe and stable operation of the multi-energy system, this invention aims to maximize the overall economic benefits of the alliance and achieve carbon emission reduction goals. It introduces key cost items such as the cyclic aging cost of shared energy storage, tiered carbon trading costs, and demand response costs. With economic optimization as the objective, a day-ahead coordinated optimization scheduling model is constructed to determine the optimal operating strategies and market trading plans for each entity in the alliance. Furthermore, an improved cost-sharing mechanism ensures the fairness and sustainability of the cooperation.

[0005] Technical Solution: A collaborative optimization scheduling approach for photovoltaic industrial parks and shared energy storage in a spot-ramp combined market, comprising the following steps:

[0006] S1. Construct an alliance operation framework consisting of multiple photovoltaic parks and shared energy storage power stations. The alliance participates in spot market, natural gas market and flexible ramp-up ancillary service market transactions as a unified market entity.

[0007] S2. Establish a shared energy storage cyclic aging model, construct a cumulative decay function based on the shared energy storage state of charge, calculate the capacity decay increment caused by charging and discharging, and form a cyclic aging cost model that can be embedded in the optimization scheduling model through piecewise linearization.

[0008] S3. Establish the objective function of the day-ahead collaborative optimization model, taking into account the net transaction cost of the spot market, gas purchase cost, operation and maintenance cost, demand response cost, aging cost of shared energy storage cycle, tiered carbon trading cost, and ramp-up market revenue;

[0009] S4. Construct multi-energy balance constraints, equipment operation constraints, callable ramp capacity constraints, and alliance power purchase and sale constraints, which together with the objective function form a complete optimization scheduling model;

[0010] S5. Establish a calculation method based on the traditional Shapley value method, enumerate all possible formation orders of the alliance, and obtain the conditions satisfied by the sub-alliance;

[0011] S6. Calculate the marginal contribution of each order according to the probability of occurrence to form the traditional Shapley initial cost allocation scheme, and obtain the initial operating cost to be allocated to each entity;

[0012] S7. Establish a method for calculating carbon emission reduction contributions, using the tiered carbon trading cost as a characteristic function, and use the Shapley value method to calculate the carbon emission responsibility allocation value of each entity, and then calculate the carbon emission reduction amount and carbon emission reduction contribution weight of each entity compared to independent operation.

[0013] S8. Construct an improved Shapley value method that considers the carbon emission reduction contribution correction factor. Construct the correction factor based on the deviation between the carbon emission reduction contribution weight and the responsibility baseline, and combine it with the environmental preference adjustment factor to adjust the initial allocation cost with rewards and penalties, forming a final allocation method that takes into account both economic efficiency and carbon emission reduction contribution.

[0014] S9. Solve the day-ahead collaborative optimization model established by S3 and S4 to obtain the alliance's electricity purchase and sale plan, gas purchase plan, park equipment output, shared energy storage charging and discharging plan, up / down ramp capacity application results, and economic items such as the alliance's total operating cost and tiered carbon trading cost for each time period.

[0015] S10. Substitute the total cost and tiered carbon trading cost obtained from S9 into the traditional cost allocation scheme established in S5-S6 and the improved cost allocation method established in S7-S8, respectively, to calculate the final cost allocation results for each photovoltaic park and shared energy storage power station, and compare and analyze the two schemes.

[0016] Furthermore, in S1, the alliance's operational framework includes multiple photovoltaic industrial parks and a shared energy storage power station. The alliance participates in day-ahead electricity, natural gas, and flexible ramp-up ancillary services markets as a unified market entity. Each park within the alliance is equipped with a photovoltaic power generation system, along with diverse integrated energy equipment such as gas turbines, gas boilers, electric boilers, power-to-gas converters, and energy and thermal storage systems to meet the various energy needs of the parks, including electricity, heat, and gas. The shared energy storage power station, as an independent flexible adjustment resource within the alliance, is not affiliated with any single park entity and primarily undertakes power regulation support and shared service functions within the alliance, providing support for the overall operational optimization of the alliance and participation in the flexible ramp-up ancillary services market.

[0017] S1.1 Operation Process

[0018] The alliance coordinates the resources of multiple stakeholders internally, optimizing all transaction and operational decisions during the day-ahead phase. Based on price signals and various forecasts, the alliance coordinates decisions regarding electricity and gas purchases, equipment output, shared energy storage charging and discharging, and ramp-up capacity applications. Under the alliance's unified dispatch framework, each park optimizes its operation through adjustments to its own equipment output and coordinated charging and discharging of shared energy storage, fully leveraging the complementary energy consumption characteristics among multiple parks and the flexible adjustment potential of shared energy storage. Simultaneously, the alliance participates in day-ahead electricity and gas market transactions as a unified entity, and, in conjunction with its overall adjustable resource capabilities, completes the application for flexible ramp-up ancillary service market capacity. Through this operational mechanism, the alliance achieves coordinated optimization of multi-stakeholder resources and unified decision-making across multiple markets.

[0019] S1.2 Market Assumptions

[0020] 1) Market Trading Rules. The consortium participates in electricity trading and flexible ramp-up ancillary services applications during the day-ahead phase, and arranges its power purchase and sale plans and ramp-up capacity based on day-ahead market prices. As a price taker, the consortium's trading activities do not affect market prices. Within the same dispatch period, the consortium can only choose one method—power purchase or power sale—and cannot engage in both simultaneously. For flexible ramp-up ancillary services, this paper assumes that the consortium's declared upward and downward ramp-up capacity can be fully recognized in the day-ahead market, and the corresponding revenue is calculated based on the declared callable capacity and capacity price, without considering compensation and assessment factors during actual dispatch.

[0021] 2) Market Prices and Transaction Boundaries. The day-ahead electricity purchase and sale price, natural gas purchase price, and flexible ramp-up ancillary service capacity price are all considered known parameters, without considering price fluctuations or the alliance's impact on market prices. The alliance can engage in electricity purchase and sale transactions with the spot electricity market and purchase natural gas through the external natural gas market. The transaction scale is constrained by the interconnection transmission capacity and natural gas supply capacity, respectively. The ramp-up capacity declared by the alliance must also meet market declaration limits and equipment operation constraints to ensure the feasibility of the declared capacity.

[0022] 3) Market Participants and Cost Accounting. The industrial park and shared energy storage form a benefit alliance and participate in day-ahead electricity trading, natural gas procurement, and flexible ramp-up ancillary service applications as a unified entity. Revenue and costs for all types of transactions are calculated based on day-ahead application results and corresponding prices, without considering intraday deviation assessments, default costs, or real-time dispatch compensation. Revenue and costs among alliance members are then allocated after the overall optimization results of the alliance are obtained.

[0023] Furthermore, in S2, to quantify the performance degradation of the energy storage battery during charge-discharge cycles, the instantaneous loss within a time period is first defined. By extracting the difference in the cumulative loss state between adjacent time points, the following can be obtained: Battery capacity degradation increment within a given time period:

[0024] (1)

[0025] In equation (1), for The increment of capacity decay at any given time; for The state of charge at any given moment; It is a non-linear cumulative decay function, representing the state at a given time. The degree of cumulative battery wear. This value is typically on the order of 10. -6 Up to 10 -5 between.

[0026] Considering the decay function Typically exhibiting a nonlinear characteristic of high at both ends and low in the middle, directly substituting it into the scheduling model can lead to difficulties in solving mixed-integer programming. To improve computational efficiency while maintaining model accuracy, it is divided into... Characterized by linear intervals:

[0027] (2)

[0028] In equation (2), This is the starting value of the interval; for In the interval The amount of change within; For interval The attenuation slope reflects the Loss sensitivity of the interval.

[0029] Based on the above attenuation increment, define Cyclic aging cost at any time as follows:

[0030] (3)

[0031] In equation (3), This represents the total investment cost of the battery. The unit battery purchase cost is set at 1000 yuan / kWh; The maximum degradation rate at which a battery is scrapped is typically taken as 0.2, meaning that when the actual usable capacity of the battery drops to 80% of its rated capacity, its cycle life is considered to have ended. Existing nonlinear aging models, such as the rainflow counting method, transform the optimization problem into a non-convex nonlinear programming problem, exponentially increasing the solution complexity. The above steps transform the nonlinear cyclic aging cost of shared energy storage into a form that can be embedded in a mixed-integer linear programming model, fundamentally solving the core pain point in existing technologies where aging cost quantification accuracy and solution efficiency are mutually exclusive. This also lays the foundation for coordinated scheduling in the spot-ramp joint market.

[0032] Furthermore, in S3, the objective function of the day-ahead collaborative optimization model takes into account the day-ahead spot electricity purchase and sale costs, external natural gas procurement costs, and revenue from flexible ramp-up ancillary service capacity application, breaking down the barriers of single-market decision-making.

[0033] (4)

[0034] In equation (4), Total operating costs of the alliance; Net transaction costs in the spot market; For gas purchase costs; For operation and maintenance costs; Cost of responding to demand; To share the aging costs of energy storage cycles; For tiered carbon trading costs; To generate revenue from the climbing market.

[0035] (1) Net transaction costs in the spot market

[0036] As a participant in the spot market, the consortium engages in electricity purchase and sale transactions with the power grid during various dispatch periods. Therefore, the consortium's net transaction costs in the spot market can be expressed as:

[0037] (5)

[0038] In equation (5), , They are respectively The power capacity of the Time Alliance for purchasing and selling electricity; , They are respectively Real-time spot electricity market purchase and sale prices.

[0039] (2) Gas purchase cost

[0040] All gas turbines and gas boilers in the various parks within the alliance consume natural gas and participate in external natural gas market transactions. Considering that the methane gas generated by the power-to-gas conversion equipment can partially substitute for externally purchased gas, the gas purchase cost is as follows:

[0041] (6)

[0042] In equation (6), For the alliance in Constantly purchasing gas volume from the external natural gas market; , , They are respectively Time Park The output electrical power of the gas turbine, the heating power of the gas boiler, and the gas production from methanation; For gas prices; , These are the gas-to-electricity conversion efficiency of the gas turbine and the thermal efficiency of the gas boiler.

[0043] (3) Operation and maintenance costs

[0044] The alliance's operation and maintenance costs mainly include two parts: the operation and maintenance costs of photovoltaic power generation, gas turbines, gas boilers, electric boilers and power-to-gas converters in the park, and the operation and maintenance costs of shared energy storage power stations, as follows:

[0045] (7)

[0046] In equation (7), , The respective operation and maintenance costs for the industrial park and shared energy storage; , They are respectively Time Park The heating capacity of the electric boiler and the power of the P2G equipment; , They are respectively It can share the charging and discharging power of energy storage at all times; , , , These are the operation and maintenance coefficients for gas turbines, gas-fired boilers, electric boilers, and P2G equipment, respectively. The operation and maintenance coefficient for shared energy storage.

[0047] (4) Demand response cost

[0048] Considering that the park can participate in load regulation through demand response resources, this section includes the compensation costs caused by demand response in the total operating cost, as expressed below:

[0049] (8)

[0050] In equation (8), , They are respectively Time Park The amount of electrical load transfer and reduction; , They are respectively Time Park The amount of heat load transferred or reduced; , These are the transferable and reduceable load factors for electrical loads, respectively. , These are the transferable and reduceable load factors for heat load, respectively.

[0051] (5) Shared energy storage cycle aging cost

[0052] Frequent charging and discharging during the internal collaboration between shared energy storage and the industrial park leads to battery life degradation. To reflect the lifespan loss of shared energy storage during the provision of charging and discharging services, its cycle aging cost is incorporated into the objective function. The cycle aging cost of shared energy storage can be expressed as:

[0053] (9)

[0054] (6) Tiered carbon trading costs

[0055] Carbon emissions are primarily considered from the carbon emissions of gas turbines and gas boilers in each industrial park, as well as the carbon emissions from electricity purchased by the consortium in the spot market. System carbon emissions are mainly reduced indirectly by replacing grid-connected electricity with photovoltaic power, and by directly absorbing and converting CO2 using power-to-gas conversion equipment.

[0056] (10)

[0057] In equation (10), , They are respectively Carbon emissions and carbon reductions of photovoltaic industrial parks at all times; , , They are respectively Time Park Carbon emissions from purchasing electricity from external power grids, gas turbines, and gas-fired boilers; for Time Park Photovoltaic power output; Carbon emission factor per unit calorific value of natural gas; It is a carbon emission factor for electricity.

[0058] (11)

[0059] In equation (11), The benchmark carbon trading price; The length of the tiered carbon trading range; This represents the growth rate of carbon trading prices.

[0060] (7) Participation in the climbing market for profit

[0061] Shared energy storage, with its rapid charging and discharging capabilities and bidirectional power regulation, possesses a certain ramp-up capability. Furthermore, the gas turbines and electric boilers within the park also have a degree of flexible adjustment capability. Therefore, they can be aggregated to form a callable ramp-up capacity and participate in the ramp-up market. Its revenue can be expressed as:

[0062] (12)

[0063] In equation (12), , They are respectively The Time Alliance can utilize ramp capacity; , These represent the unit ramp-up service prices. The above steps, on a day-ahead timescale, comprehensively consider day-ahead spot electricity purchase and sale costs, external natural gas procurement costs, and revenue from flexible ramp-up ancillary service capacity declarations, breaking down barriers to single-market decision-making and maximizing the marginal benefits of diverse flexible resources (electricity, heat, gas, and storage) in a multi-dimensional market. Furthermore, considering the aging costs of shared energy storage cycles and tiered carbon trading costs, the resulting coordinated dispatch scheme not only possesses higher overall economic efficiency.

[0064] Furthermore, S4 includes constraints such as multi-energy balancing, park equipment operation, available ramp-up capacity, alliance power purchase and sale, and basic operation of shared energy storage:

[0065] (1) Multi-energy equilibrium constraint

[0066] 1) Alliance electrical balance constraints

[0067] The alliance power balance constraint is used to describe the power conservation relationship between photovoltaic power generation equipment, conversion equipment and energy storage equipment, shared energy storage and the power grid in the park. Its expression is:

[0068] (12)

[0069] In equation (12), , They are respectively Time Park The charging and discharging power of energy storage devices; , , They are respectively Time Park The base load, transferable load, and load reduction values ​​of the electrical load; , They are respectively It can share the charging and discharging power of the energy storage power station at all times.

[0070] 2) Thermal balance constraints in the park

[0071] Considering that thermal energy usually has strong regional locality, thermal balance constraints are established separately for each park.

[0072] (13)

[0073] In equation (13), , They are respectively Time Park Thermal power of gas turbines and electric boilers; , They are respectively Time Park The heat absorption and release power of the thermal storage equipment; , , They are respectively Time Park The base load, transferable load, and reduceable load values ​​of the heat load.

[0074] (2) Constraints on the operation of equipment in the park

[0075] The basic operating constraints of each piece of equipment in the park are as follows:

[0076] (14)

[0077] In equation (14), , , , , , These are the upper and lower limits of output for gas turbines, gas boilers, and P2G equipment, respectively. , These are the upper and lower limits of transferable load; This is the upper limit for load reduction; for Time Park Gas turbine start / stop indicator: 1 indicates start-up, 0 indicates shutdown; For the park 0-1 variables that can reduce load.

[0078] Furthermore, considering the mechanical inertia of gas turbines, it is necessary to consider the physical ramp rate constraints between adjacent time periods, as detailed below:

[0079] (15)

[0080] In equation (15), , They are respectively Time Park The uphill and downhill ramp rates of the gas turbine.

[0081] (3) The ramp capacity constraint can be invoked.

[0082] (16)

[0083] In equation (16), , They are respectively Time Park Available ramp-up capacity for gas turbines and electric boilers; , Time Park The available downhill ramp capacity of gas turbines and electric boilers; , They are respectively The available uphill and downhill ramp capacity of the shared energy storage is always available.

[0084] In addition, the alliance's available ramp-up and ramp-down capacity is also subject to market reporting limits.

[0085] (17)

[0086] In equation (17), , These represent the maximum values ​​of the market's declared uphill and downhill ramp capacity, respectively.

[0087] 1) Gas turbine

[0088] Considering the impact of flexible ramping services on available equipment capacity, when gas turbines participate in the ramping market, the reserved upward ramping capacity will reduce the remaining upward ramping capacity of the compressor unit, while the reserved downward ramping capacity will reduce the downward ramping margin of the unit. Therefore, its energy output and ramping reserve capacity must simultaneously meet the constraints of the equipment's operational range, as detailed below:

[0089] (18)

[0090] In addition, the uphill and downhill ramp capacity available for the gas turbine must also meet the ramp rate limit of the unit.

[0091] (19)

[0092] 2) Electric boiler

[0093] Electric boilers are essentially flexible electrical loads, and their ramp-up adjustment direction is opposite to that of power generation equipment. When providing ramp-up capability, electric boilers essentially release electricity by reducing power consumption; when providing ramp-down capability, they absorb more electrical energy by increasing power consumption. Their capacity boundary constraints are as follows:

[0094] (20)

[0095] In equation (20), , These are the upper and lower limits of the electric boiler's output; For the thermal efficiency of electric boilers.

[0096] Furthermore, considering that the participation of electric boilers in the ramp-up market will cause real-time changes in their power consumption and heat production, thus introducing additional disturbances to the thermal system, to ensure the physical feasibility of the day-ahead scheduling results even when ramp-up capacity is called up, corresponding thermal regulation capacity needs to be reserved within the system. This capacity will be shared by gas-fired boilers, gas turbines, and thermal storage equipment. When electric boilers provide ramp-up services, their power consumption decreases, and their heat production decreases accordingly, potentially leading to a heat deficit in the system. Therefore, this heat deficit should be compensated by the remaining available additional heat production capacity of gas-fired boilers, the additional heating capacity brought about by the increased output of gas turbines, and the heat release capacity of thermal storage equipment. Based on this, constraints need to be established on the heat compensation capacity after ramp-up is called up, overcoming the drawbacks of traditional models that deviate from thermal balance and ensuring the physical feasibility of the scheduling scheme under actual day-ahead calls.

[0097] (twenty one)

[0098] In equation (21), For the thermal efficiency of the gas turbine; for Time Park Heat release indicator for thermal storage equipment; The heat release efficiency of the thermal storage equipment; This refers to the rated capacity of the thermal storage equipment; , They are respectively Time Park The state of charge and lower limit of the thermal storage equipment.

[0099] When an electric boiler provides downhill service, it will generate additional heat after increasing its power consumption. To ensure the balance of the thermal system, this additional heat needs to be absorbed through methods such as reducing heating supply from the gas boiler, simultaneously reducing heat output during the downhill process of the gas turbine, and absorbing heat through thermal storage equipment. Specific constraints are as follows:

[0100] (twenty two)

[0101] In equation (22), for Time Park Heat absorption markings on thermal storage equipment; The heat absorption efficiency of the thermal storage equipment; This represents the upper limit of the state of charge of the thermal storage device.

[0102] 3) Shared energy storage

[0103] When shared energy storage participates in the ramp-up market, its available ramp-up capacity is limited by both the rated charge / discharge power of the equipment and its current operating power, as well as by the energy storage's state of charge. Specifically, the ramp-up capacity corresponds to the energy storage's ability to increase the system's net injected power, while the ramp-down capacity corresponds to the energy storage's ability to decrease the system's net injected power. Therefore, corresponding power boundary constraints must be met, as detailed below:

[0104] (twenty three)

[0105] In equation (23), , This represents the maximum value of charging and discharging for shared energy storage.

[0106] Furthermore, considering that ramp-up services typically need to maintain an effective response for a certain period, shared energy storage should have sufficient available power when providing ramp-up services and sufficient remaining charging capacity when providing downhill services. Based on this, further energy support constraints need to be constructed, as follows:

[0107] (twenty four)

[0108] In equation (24), , , They are respectively The state of charge of the energy storage power station at any given time and its minimum and maximum values; The rated capacity of the shared energy storage power station; , These are the charging and discharging efficiencies of shared energy storage, respectively. , They are respectively Share the actual maximum ramp capacity of energy storage at all times; , They are respectively The energy storage capacity can be accessed at any time for ramping up.

[0109] (4) Constraints on the purchase and sale of electricity by the consortium

[0110] To prevent the alliance from simultaneously purchasing and selling electricity during the same period, and to ensure that its external transaction power does not exceed the market declaration limit, the following constraints are established for the alliance's electricity purchase and sale:

[0111] (25)

[0112] In equation (25), , These represent the maximum values ​​for the alliance's external purchases and sales of electricity, respectively. for The 0-1 variable for the Moment Alliance's participation in spot electricity market transactions, when At that time, the alliance purchased electricity from abroad. At that time, the alliance sold electricity to external parties.

[0113] (5) Basic operational constraints of shared energy storage

[0114] (26)

[0115] In equation (26), , These are the charging and discharging flags of the shared energy storage power station, both Boolean variables. The callable ramp-up capacity constraint constructed in the steps quantifies the ramp-up contributions of the gas turbine, electric boiler, and shared energy storage in both upward and downward directions, and establishes a system compensation capability constraint for system fluctuations caused by the electric boiler's participation in ramp-up. Existing technologies typically only consider equipment power boundaries or simple standby capacity, neglecting the thermal balance feasibility of ramp-up capacity call-up. The constraint system of this invention ensures that the previously declared ramp-up capacity is physically feasible, significantly improving the safety and reliability of electro-thermal coupled systems participating in the flexible ramp-up market.

[0116] Furthermore, in step S5, all possible formation orders of the alliance are enumerated to derive the conditions satisfied by the sub-alliances. Assume that the interest alliance is formed by... The alliance consists of several independent decision-making entities, denoted as the complete set of the alliance entities. ,in:

[0117] (1) Main body For photovoltaic parks participating in the alliance, each entity independently owns the ownership and scheduling decision-making rights of energy equipment such as photovoltaics, gas turbines, and electric boilers within the park, and independently bears the energy demand and operating costs within the park;

[0118] (2) Main body As the operating entity of the shared energy storage power station, it independently owns the ownership and operation rights of the shared energy storage power station and provides power regulation and ramp-up service support to the alliance.

[0119] Any non-empty subset in a consortium Called a sub-alliance, when This refers to the entire alliance at the time. Furthermore, the cooperative energy supply model studied involves multiple stakeholders, with a reasonable distribution of benefits based on each stakeholder's contribution to the cooperative project. The revenue equals the mean marginal contribution of the alliance. Assume... For the Alliance The minimum total operating cost after participating in market-coordinated operations. The following formula should be satisfied: the total cost of multi-entity collaborative operation should not exceed the sum of the costs of each entity operating independently.

[0120] (27)

[0121] The above steps use the traditional Shapley value method to calculate the initial cost allocation results of each entity, in order to quantify the initial marginal contribution of each member to the overall benefits of the alliance. This provides the mathematical basis and calculation basis for the next step of introducing a correction mechanism for environmental rights and carbon emission reduction contributions.

[0122] Furthermore, in step S6, a traditional Shapley initial cost allocation scheme is formed, and the allocation formula is as follows:

[0123] (28)

[0124] In equation (28), These are weighting coefficients, reflecting the sub-alliance The probability of appearing in all alliance combinations; As the main body of the alliance Operating costs allocated using the traditional Shapley value method; The total number of members; For the alliance Number of members; as the main body Pair Alliance The marginal cost contribution.

[0125] Judgment criteria:

[0126] (29)

[0127] In equation (29), This represents the total cost for all participating parties. The sum of the costs shared by all entities within the alliance is exactly equal to the minimum total operating cost for the entire alliance to operate collaboratively.

[0128] (30)

[0129] In equation (30), as the main body The minimum operating cost for independent market participation. This criterion states that the total cost shared by any entity participating in the alliance is no higher than the total cost of operating independently in the market, ensuring that all entities participating in the alliance can achieve cost reduction.

[0130] Furthermore, in S7, a method for calculating carbon emission reduction contributions is established, overcoming the limitation of existing technologies that cannot objectively separate individual emission reduction contributions, and providing an accurate mathematical basis for subsequent rewards and penalties based on emission reduction contribution levels. To quantify the actual contribution of each entity to the overall low-carbon operation of the alliance, the tiered carbon trading cost is defined as a new characteristic function. Using the same marginal accounting logic as economic cost allocation, the main body... Carbon emission responsibility sharing in the alliance It can be represented as:

[0131] (31)

[0132] Define the subject The reduction in carbon emissions resulting from participation in collaboration and their corresponding carbon emission reduction contribution weights Specifically as follows:

[0133] (32)

[0134] In equation (32), as the main body The tiered carbon emission costs of independent operation. Within the traditional Shapley marginal cost calculation framework, a carbon emission reduction contribution weighting coefficient is introduced to accurately quantify the actual contribution of each entity to the overall low-carbon operation of the consortium. This step overcomes the limitation of existing technologies that cannot objectively separate individual emission reduction contributions, providing an accurate mathematical basis for subsequent rewards and penalties for environmental rights.

[0135] Furthermore, in step S8, the method for coordinated optimization scheduling of photovoltaic parks and shared energy storage oriented towards a spot-ramp joint market according to claim 1 is characterized in that step S8 includes constructing an improved Shapley value method that considers a carbon emission reduction contribution correction factor:

[0136] The traditional Shapley apportionment model implicitly assumes that the responsibilities and contributions of each alliance member in environmental protection are absolutely equal, meaning that the contribution weights are all equal. However, due to significant physical differences in the installed capacity of equipment such as gas turbines and electric boilers among the photovoltaic parks participating in the alliance, a main body is defined to eliminate the allocation bias caused by the equalization assumption. The deviation of carbon emission reduction contribution is used as a contribution correction factor, as detailed below:

[0137] (33)

[0138] In equation (33), Contributes a correction factor to carbon emission reduction, when When the target is met, it indicates that the entity has exceeded its emission reduction target and will be rewarded with economic incentives; otherwise, it will be penalized with economic incentives. This serves as the baseline for responsibility.

[0139] (34)

[0140] In equation (34), The alliance is comprised of photovoltaic industrial parks. For shared energy storage.

[0141] Based on the carbon emission reduction contribution correction factor, the initial allocated costs of the main entities are calculated, overcoming the limitation of traditional methods that cannot reflect differences in environmental responsibility. The final total operating cost that needs to be borne as follows:

[0142] (35)

[0143] In equation (35), An environmental preference adjustment factor was used. The initial allocation results were adjusted using a carbon emission reduction contribution correction factor, establishing a low-carbon reward and punishment mechanism within the alliance. While maintaining the overall balance of the alliance's revenue and expenditure, this mechanism achieves economic compensation for high-contributing entities and economic penalties for high-carbon-emitting entities, overcoming the limitations of traditional methods that cannot reflect differences in environmental responsibility.

[0144] The present invention provides a method for coordinated and optimized scheduling of photovoltaic industrial parks and shared energy storage in a spot-ramp joint market. Compared with the prior art, the beneficial effects of the present invention are as follows:

[0145] 1) This invention overcomes the problems of insufficient photovoltaic absorption and low utilization of energy storage resources caused by the fragmented scheduling of the spot electricity market and the flexible ramp-up ancillary service market. By establishing a cyclic aging cumulative degradation model with state of charge as the core, and using piecewise linearization technology to embed the full life cycle cyclic aging cost into the optimized scheduling framework, it effectively avoids premature battery scrapping caused by overcharging and discharging in pursuit of short-term market gains. At the same time, it breaks down the decision-making barriers between the electricity market and the ramp-up market, and jointly optimizes ramp-up capacity application, day-ahead power purchase and sale plans, and energy storage charging and discharging strategies. While ensuring the revenue of the electricity market, it also taps into the ramp-up service value brought by the fluctuation characteristics of photovoltaic output and the rapid response capability of energy storage, thereby improving the overall revenue of the alliance.

[0146] 2) This invention overcomes the problems of traditional Shapley profit-sharing mechanisms, which only consider economic contributions and fail to reflect the value of carbon emission reduction, resulting in poor fairness, insufficient stability, and weak incentives for renewable energy consumption. It establishes an improved Shapley cost-sharing mechanism that balances economic contributions and carbon emission reduction responsibilities, enhancing the transparency and fairness of profit-sharing, incentivizing all participating entities to proactively optimize operations and increase the proportion of renewable energy consumption, strengthening the long-term stability of the alliance, and providing sustainable profit guarantees for the market-oriented operation of multi-entity integrated energy systems. Attached Figure Description

[0147] Figure 1 A collaborative optimization operation framework for photovoltaic industrial parks and shared energy storage, oriented towards a combined spot and ramp-up market.

[0148] Figure 2 This embodiment of the invention relates to the projected photovoltaic output, electric heating base load, and market price of industrial parks 1-3.

[0149] Figure 3 The power balance results of the alliance in the embodiments of the present invention,

[0150] Figure 4 In this embodiment of the invention, the results of heat balance and natural gas balance in parks 1-3 are as follows:

[0151] Figure 5 The operational results of energy storage, thermal storage, and shared energy storage in parks 1-3 of this invention are presented in this embodiment.

[0152] Figure 6 This represents the electricity demand response results for parks 1-3 in this embodiment of the invention.

[0153] Figure 7 The thermal demand response results for parks 1-3 in this embodiment of the invention are as follows.

[0154] Figure 8 This refers to the changes in the alliance's power purchase and sale behavior and ramp-up capability in this embodiment of the invention.

[0155] Figure 9 This is a flowchart of the method of the present invention. Detailed Implementation

[0156] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the embodiments described.

[0157] Example: Figure 1 As shown, this invention presents a collaborative optimization scheduling method for photovoltaic industrial parks and shared energy storage in a spot-ramp market. The invention aims to minimize the overall operating cost of the alliance and guides cost sharing among alliance members based on carbon emission reduction responsibilities. By embedding a piecewise linearized cyclic aging cumulative decay model into the joint optimization of electricity and the ramp market, it achieves deep multi-market collaboration under precise quantification of energy storage cyclic aging costs, as well as fair and stable cost sharing that balances economic contribution and carbon emission reduction responsibilities. This invention includes the following steps:

[0158] S1. Construct an alliance operation framework consisting of multiple photovoltaic parks and shared energy storage power stations. The alliance participates in spot market, natural gas market and flexible ramp-up ancillary service market transactions as a unified market entity.

[0159] S2. Establish a shared energy storage cyclic aging model, construct a cumulative decay function based on the shared energy storage state of charge, calculate the capacity decay increment caused by charging and discharging, and form a cyclic aging cost model that can be embedded in the optimization scheduling model through piecewise linearization.

[0160] S3. Establish the objective function of the day-ahead collaborative optimization model, taking into account the net transaction cost of the spot market, gas purchase cost, operation and maintenance cost, demand response cost, aging cost of shared energy storage cycle, tiered carbon trading cost, and ramp-up market revenue;

[0161] S4. Construct multi-energy balance constraints, equipment operation constraints, callable ramp capacity constraints, and alliance power purchase and sale constraints, which together with the objective function form a complete optimization scheduling model;

[0162] S5. Establish a calculation method based on the traditional Shapley value method, enumerate all possible formation orders of the alliance, and obtain the conditions satisfied by the sub-alliance;

[0163] S6. Calculate the marginal contribution of each order according to the probability of occurrence to form the traditional Shapley initial cost allocation scheme, and obtain the initial operating cost to be allocated to each entity;

[0164] S7. Establish a method for calculating carbon emission reduction contributions, using the tiered carbon trading cost as a characteristic function, and use the Shapley value method to calculate the carbon emission responsibility allocation value of each entity, and then calculate the carbon emission reduction amount and carbon emission reduction contribution weight of each entity compared to independent operation.

[0165] S8. Construct an improved Shapley value method that considers the carbon emission reduction contribution correction factor. Construct the correction factor based on the deviation between the carbon emission reduction contribution weight and the responsibility baseline, and combine it with the environmental preference adjustment factor to adjust the initial allocation cost with rewards and penalties, forming a final allocation method that takes into account both economic efficiency and carbon emission reduction contribution.

[0166] S9. Solve the day-ahead collaborative optimization model established by S3 and S4 to obtain the alliance's electricity purchase and sale plan, gas purchase plan, park equipment output, shared energy storage charging and discharging plan, up / down ramp capacity application results, and economic items such as the alliance's total operating cost and tiered carbon trading cost for each time period.

[0167] S10. Substitute the total cost and tiered carbon trading cost obtained from S9 into the traditional cost allocation scheme established in S5-S6 and the improved cost allocation method established in S7-S8, respectively, to calculate the final cost allocation results for each photovoltaic park and shared energy storage power station, and compare and analyze the two schemes.

[0168] Furthermore, in S1, the alliance's operational framework includes multiple photovoltaic industrial parks and a shared energy storage power station. The alliance participates in day-ahead electricity, natural gas, and flexible ramp-up ancillary services markets as a unified market entity. Each park within the alliance is equipped with a photovoltaic power generation system, along with diverse integrated energy equipment such as gas turbines, gas boilers, electric boilers, power-to-gas converters, and energy and thermal storage systems to meet the various energy needs of the parks, including electricity, heat, and gas. The shared energy storage power station, as an independent flexible adjustment resource within the alliance, is not affiliated with any single park entity and primarily undertakes power regulation support and shared service functions within the alliance, providing support for the overall operational optimization of the alliance and participation in the flexible ramp-up ancillary services market.

[0169] S1.1 Operation Process

[0170] The alliance coordinates the resources of multiple stakeholders internally, optimizing all transaction and operational decisions during the day-ahead phase. Based on price signals and various forecasts, the alliance coordinates decisions regarding electricity and gas purchases, equipment output, shared energy storage charging and discharging, and ramp-up capacity applications. Under the alliance's unified dispatch framework, each park optimizes its operation through adjustments to its own equipment output and coordinated charging and discharging of shared energy storage, fully leveraging the complementary energy consumption characteristics among multiple parks and the flexible adjustment potential of shared energy storage. Simultaneously, the alliance participates in day-ahead electricity and gas market transactions as a unified entity, and, in conjunction with its overall adjustable resource capabilities, completes the application for flexible ramp-up ancillary service market capacity. Through this operational mechanism, the alliance achieves coordinated optimization of multi-stakeholder resources and unified decision-making across multiple markets.

[0171] S1.2 Market Assumptions

[0172] 1) Market Trading Rules. The consortium participates in electricity trading and flexible ramp-up ancillary services applications during the day-ahead phase, and arranges its power purchase and sale plans and ramp-up capacity based on day-ahead market prices. As a price taker, the consortium's trading activities do not affect market prices. Within the same dispatch period, the consortium can only choose one method—power purchase or power sale—and cannot engage in both simultaneously. For flexible ramp-up ancillary services, this paper assumes that the consortium's declared upward and downward ramp-up capacity can be fully recognized in the day-ahead market, and the corresponding revenue is calculated based on the declared callable capacity and capacity price, without considering compensation and assessment factors during actual dispatch.

[0173] 2) Market Prices and Transaction Boundaries. The day-ahead electricity purchase and sale price, natural gas purchase price, and flexible ramp-up ancillary service capacity price are all considered known parameters, without considering price fluctuations or the alliance's impact on market prices. The alliance can engage in electricity purchase and sale transactions with the spot electricity market and purchase natural gas through the external natural gas market. The transaction scale is constrained by the interconnection transmission capacity and natural gas supply capacity, respectively. The ramp-up capacity declared by the alliance must also meet market declaration limits and equipment operation constraints to ensure the feasibility of the declared capacity.

[0174] 3) Market Participants and Cost Accounting. The industrial park and shared energy storage form a benefit alliance and participate in day-ahead electricity trading, natural gas procurement, and flexible ramp-up ancillary service applications as a unified entity. Revenue and costs for all types of transactions are calculated based on day-ahead application results and corresponding prices, without considering intraday deviation assessments, default costs, or real-time dispatch compensation. Revenue and costs among alliance members are then allocated after the overall optimization results of the alliance are obtained.

[0175] Furthermore, in S2, to quantify the performance degradation of the energy storage battery during charge-discharge cycles, the instantaneous loss within a time period is first defined. By extracting the difference in the cumulative loss state between adjacent time points, the following can be obtained: Battery capacity degradation increment within a given time period:

[0176] (1)

[0177] In equation (1), for The increment of capacity decay at any given time; for The state of charge at any given moment; It is a non-linear cumulative decay function, representing the state at a given time. The degree of cumulative battery wear. This value is typically on the order of 10. -6 Up to 10 -5 between.

[0178] Considering the decay function Typically exhibiting a nonlinear characteristic of high at both ends and low in the middle, directly substituting it into the scheduling model can lead to difficulties in solving mixed-integer programming. To improve computational efficiency while maintaining model accuracy, it is divided into... Characterized by linear intervals:

[0179] (2)

[0180] In equation (2), This is the starting value of the interval; for In the interval The amount of change within; For interval The attenuation slope reflects the Loss sensitivity of the interval.

[0181] Based on the above attenuation increment, define Cyclic aging cost at any time as follows:

[0182] (3)

[0183] In equation (3), This represents the total investment cost of the battery. The unit battery purchase cost is set at 1000 yuan / kWh; This is the maximum degradation rate when the battery is scrapped, usually taken as 0.2. That is, when the actual usable capacity of the battery drops to 80% of the rated capacity, its cycle life is considered to have ended.

[0184] Furthermore, in S3, the objective function for establishing the day-ahead collaborative optimization model is:

[0185] (4)

[0186] In equation (4), Total operating costs of the alliance; Net transaction costs in the spot market; For gas purchase costs; For operation and maintenance costs; Cost of responding to demand; To share the aging costs of energy storage cycles; For tiered carbon trading costs; To generate revenue from the climbing market.

[0187] (1) Net transaction costs in the spot market

[0188] As a participant in the spot market, the consortium engages in electricity purchase and sale transactions with the power grid during various dispatch periods. Therefore, the consortium's net transaction costs in the spot market can be expressed as:

[0189] (5)

[0190] In equation (5), , They are respectively The power capacity of the Time Alliance for purchasing and selling electricity; , They are respectively Real-time spot electricity market purchase and sale prices.

[0191] (2) Gas purchase cost

[0192] All gas turbines and gas boilers in the various parks within the alliance consume natural gas and participate in external natural gas market transactions. Considering that the methane gas generated by the power-to-gas conversion equipment can partially substitute for externally purchased gas, the gas purchase cost is as follows:

[0193] (6)

[0194] In equation (6), For the alliance in Constantly purchasing gas volume from the external natural gas market; , , They are respectively Time Park The output electrical power of the gas turbine, the heating power of the gas boiler, and the gas production from methanation; For gas prices; , These are the gas-to-electricity conversion efficiency of the gas turbine and the thermal efficiency of the gas boiler.

[0195] (3) Operation and maintenance costs

[0196] The alliance's operation and maintenance costs mainly include two parts: the operation and maintenance costs of photovoltaic power generation, gas turbines, gas boilers, electric boilers and power-to-gas converters in the park, and the operation and maintenance costs of shared energy storage power stations, as follows:

[0197] (7)

[0198] In equation (7), , The respective operation and maintenance costs for the industrial park and shared energy storage; , They are respectively Time Park The heating capacity of the electric boiler and the power of the P2G equipment; , They are respectively It can share the charging and discharging power of energy storage at all times; , , , These are the operation and maintenance coefficients for gas turbines, gas-fired boilers, electric boilers, and P2G equipment, respectively. The operation and maintenance coefficient for shared energy storage.

[0199] (4) Demand response cost

[0200] Considering that the park can participate in load regulation through demand response resources, this section includes the compensation costs caused by demand response in the total operating cost, as expressed below:

[0201] (8)

[0202] In equation (8), , They are respectively Time Park The amount of electrical load transfer and reduction; , They are respectively Time Park The amount of heat load transferred or reduced; , These are the transferable and reduceable load factors for electrical loads, respectively. , These are the transferable and reduceable load factors for heat load, respectively.

[0203] (5) Shared energy storage cycle aging cost

[0204] Frequent charging and discharging during the internal collaboration between shared energy storage and the industrial park leads to battery life degradation. To reflect the lifespan loss of shared energy storage during the provision of charging and discharging services, its cycle aging cost is incorporated into the objective function. The cycle aging cost of shared energy storage can be expressed as:

[0205] (9)

[0206] (6) Tiered carbon trading costs

[0207] Carbon emissions are primarily considered from the carbon emissions of gas turbines and gas boilers in each industrial park, as well as the carbon emissions from electricity purchased by the consortium in the spot market. System carbon emissions are mainly reduced indirectly by replacing grid-connected electricity with photovoltaic power, and by directly absorbing and converting CO2 using power-to-gas conversion equipment.

[0208] (10)

[0209] In equation (10), , They are respectively Carbon emissions and carbon reductions of photovoltaic industrial parks at all times; , , They are respectively Time Park Carbon emissions from purchasing electricity from external power grids, gas turbines, and gas-fired boilers; for Time Park Photovoltaic power output; Carbon emission factor per unit calorific value of natural gas; It is a carbon emission factor for electricity.

[0210] (11)

[0211] In equation (11), The benchmark carbon trading price; The length of the tiered carbon trading range; This represents the growth rate of carbon trading prices.

[0212] (7) Participation in the climbing market for profit

[0213] Shared energy storage, with its rapid charging and discharging capabilities and bidirectional power regulation, possesses a certain ramp-up capability. Furthermore, the gas turbines and electric boilers within the park also have a degree of flexible adjustment capability. Therefore, they can be aggregated to form a callable ramp-up capacity and participate in the ramp-up market. Its revenue can be expressed as:

[0214] (12)

[0215] In equation (12), , They are respectively The Time Alliance can utilize ramp capacity; , These are the unit prices for hill climbing services.

[0216] Furthermore, S4 includes constraints such as multi-energy balancing, park equipment operation, available ramp-up capacity, alliance power purchase and sale, and basic operation of shared energy storage:

[0217] (1) Multi-energy equilibrium constraint

[0218] 1) Alliance electrical balance constraints

[0219] The alliance power balance constraint is used to describe the power conservation relationship between photovoltaic power generation equipment, conversion equipment and energy storage equipment, shared energy storage and the power grid in the park. Its expression is:

[0220] (12)

[0221] In equation (12), , They are respectively Time Park The charging and discharging power of energy storage devices; , , They are respectively Time Park The base load, transferable load, and load reduction values ​​of the electrical load; , They are respectively It can share the charging and discharging power of the energy storage power station at all times.

[0222] 2) Thermal balance constraints in the park

[0223] Considering that thermal energy usually has strong regional locality, thermal balance constraints are established separately for each park.

[0224] (13)

[0225] In equation (13), , They are respectively Time Park Thermal power of gas turbines and electric boilers; , They are respectively Time Park The heat absorption and release power of the thermal storage equipment; , , They are respectively Time Park The base load, transferable load, and reduceable load values ​​of the heat load.

[0226] (2) Constraints on the operation of equipment in the park

[0227] The basic operating constraints of each piece of equipment in the park are as follows:

[0228] (14)

[0229] In equation (14), , , , , , These are the upper and lower limits of output for gas turbines, gas boilers, and P2G equipment, respectively. , These are the upper and lower limits of transferable load; This is the upper limit for load reduction; for Time Park Gas turbine start / stop indicator: 1 indicates start-up, 0 indicates shutdown; For the park 0-1 variables that can reduce load.

[0230] Furthermore, considering the mechanical inertia of gas turbines, it is necessary to consider the physical ramp rate constraints between adjacent time periods, as detailed below:

[0231] (15)

[0232] In equation (15), , They are respectively Time Park The uphill and downhill ramp rates of the gas turbine.

[0233] (3) The ramp capacity constraint can be invoked.

[0234] (16)

[0235] In equation (16), , They are respectively Time Park Available ramp-up capacity for gas turbines and electric boilers; , Time Park The available downhill ramp capacity of gas turbines and electric boilers; , They are respectively The available uphill and downhill ramp capacity of the shared energy storage is always available.

[0236] In addition, the alliance's available ramp-up and ramp-down capacity is also subject to market reporting limits.

[0237] (17)

[0238] In equation (17), , These represent the maximum values ​​of the market's declared uphill and downhill ramp capacity, respectively.

[0239] 1) Gas turbine

[0240] Considering the impact of flexible ramping services on available equipment capacity, when gas turbines participate in the ramping market, the reserved upward ramping capacity will reduce the remaining upward ramping capacity of the compressor unit, while the reserved downward ramping capacity will reduce the downward ramping margin of the unit. Therefore, its energy output and ramping reserve capacity must simultaneously meet the constraints of the equipment's operational range, as detailed below:

[0241] (18)

[0242] In addition, the uphill and downhill ramp capacity available for the gas turbine must also meet the ramp rate limit of the unit.

[0243] (19)

[0244] 2) Electric boiler

[0245] Electric boilers are essentially flexible electrical loads, and their ramp-up adjustment direction is opposite to that of power generation equipment. When providing ramp-up capability, electric boilers essentially release electricity by reducing power consumption; when providing ramp-down capability, they absorb more electrical energy by increasing power consumption. Their capacity boundary constraints are as follows:

[0246] (20)

[0247] In equation (20), , These are the upper and lower limits of the electric boiler's output; For the thermal efficiency of electric boilers.

[0248] Furthermore, considering that the participation of electric boilers in the ramp-up market will cause real-time changes in their power consumption and heat production, thus introducing additional disturbances to the thermal system, to ensure the physical feasibility of day-ahead dispatching results even when ramp-up capacity is called up, corresponding thermal regulation capacity needs to be reserved within the system. This capacity should be shared by gas-fired boilers, gas turbines, and thermal storage equipment. When electric boilers provide ramp-up services, their power consumption decreases, and their heat production decreases accordingly, potentially leading to a heat deficit in the system. Therefore, this heat deficit should be compensated by the remaining available heating capacity of gas-fired boilers, the additional heating capacity brought about by the increased output of gas turbines, and the heat release capacity of thermal storage equipment. Based on this, constraints need to be established on the heat compensation capacity after ramp-up calls to ensure the safe and stable operation of the thermal system.

[0249] (twenty one)

[0250] In equation (21), For the thermal efficiency of the gas turbine; for Time Park Heat release indicator for thermal storage equipment; The heat release efficiency of the thermal storage equipment; This refers to the rated capacity of the thermal storage equipment; , They are respectively Time Park The state of charge and lower limit of the thermal storage equipment.

[0251] When an electric boiler provides downhill service, it will generate additional heat after increasing its power consumption. To ensure the balance of the thermal system, this additional heat needs to be absorbed through methods such as reducing heating supply from the gas boiler, simultaneously reducing heat output during the downhill process of the gas turbine, and absorbing heat through thermal storage equipment. Specific constraints are as follows:

[0252] (twenty two)

[0253] In equation (22), for Time Park Heat absorption markings on thermal storage equipment; The heat absorption efficiency of the thermal storage equipment; This represents the upper limit of the state of charge of the thermal storage device.

[0254] 3) Shared energy storage

[0255] When shared energy storage participates in the ramp-up market, its available ramp-up capacity is limited by both the rated charge / discharge power of the equipment and its current operating power, as well as by the energy storage's state of charge. Specifically, the ramp-up capacity corresponds to the energy storage's ability to increase the system's net injected power, while the ramp-down capacity corresponds to the energy storage's ability to decrease the system's net injected power. Therefore, corresponding power boundary constraints must be met, as detailed below:

[0256] (twenty three)

[0257] In equation (23), , This represents the maximum value of charging and discharging for shared energy storage.

[0258] Furthermore, considering that ramp-up services typically need to maintain an effective response for a certain period, shared energy storage should have sufficient available power when providing ramp-up services and sufficient remaining charging capacity when providing downhill services. Based on this, further energy support constraints need to be constructed, as follows:

[0259] (twenty four)

[0260] In equation (24), , , They are respectively The state of charge of the energy storage power station at any given time and its minimum and maximum values; The rated capacity of the shared energy storage power station; , These are the charging and discharging efficiencies of shared energy storage, respectively. , They are respectively Share the actual maximum ramp capacity of energy storage at all times; , They are respectively The energy storage capacity can be accessed at any time for ramping up.

[0261] (4) Constraints on the purchase and sale of electricity by the consortium

[0262] To prevent the alliance from simultaneously purchasing and selling electricity during the same period, and to ensure that its external transaction power does not exceed the market declaration limit, the following constraints are established for the alliance's electricity purchase and sale:

[0263] (25)

[0264] In equation (25), , These represent the maximum values ​​for the alliance's external purchases and sales of electricity, respectively. for The 0-1 variable for the Moment Alliance's participation in spot electricity market transactions, when At that time, the alliance purchased electricity from abroad. At that time, the alliance sold electricity to external parties.

[0265] (5) Basic operational constraints of shared energy storage

[0266] (26)

[0267] In equation (26), , These are the charging and discharging flags for the shared energy storage power station, both of which are Boolean variables.

[0268] Furthermore, in step S5, all possible formation orders of the alliance are enumerated to derive the conditions satisfied by the sub-alliances. Assume that the interest alliance is formed by... The alliance consists of several independent decision-making entities, denoted as the complete set of the alliance entities. ,in:

[0269] (1) Main body For photovoltaic parks participating in the alliance, each entity independently owns the ownership and scheduling decision-making rights of energy equipment such as photovoltaics, gas turbines, and electric boilers within the park, and independently bears the energy demand and operating costs within the park;

[0270] (2) Main body As the operating entity of the shared energy storage power station, it independently owns the ownership and operation rights of the shared energy storage power station and provides power regulation and ramp-up service support to the alliance.

[0271] Any non-empty subset in a consortium Called a sub-alliance, when This refers to the entire alliance at the time. Furthermore, the cooperative energy supply model studied involves multiple stakeholders, with a reasonable distribution of benefits based on each stakeholder's contribution to the cooperative project. The revenue equals the mean marginal contribution of the alliance. Assume... For the Alliance The minimum total operating cost after participating in market-coordinated operations. The following formula should be satisfied: the total cost of multi-entity collaborative operation should not exceed the sum of the costs of each entity operating independently.

[0272] (27)

[0273] Furthermore, in step S6, a traditional Shapley initial cost allocation scheme is formed, and the allocation formula is as follows:

[0274] (28)

[0275] In equation (28), These are weighting coefficients, reflecting the sub-alliance The probability of appearing in all alliance combinations; As the main body of the alliance Operating costs allocated using the traditional Shapley value method; The total number of members; For the alliance Number of members; as the main body Pair Alliance The marginal cost contribution.

[0276] Judgment criteria:

[0277] (29)

[0278] In equation (29), This represents the total cost for all participating parties. The sum of the costs shared by all entities within the alliance is exactly equal to the minimum total operating cost for the entire alliance to operate collaboratively.

[0279] (30)

[0280] In equation (30), as the main body The minimum operating cost for independent market participation. This criterion states that the total cost shared by any entity participating in the alliance is no higher than the total cost of operating independently in the market, ensuring that all entities participating in the alliance can achieve cost reduction.

[0281] Furthermore, in S7, a method for calculating carbon emission reduction contributions is established. To quantify the actual contribution of each entity to the overall low-carbon operation of the alliance, the tiered carbon trading cost is defined as a new characteristic function. Using the same marginal accounting logic as economic cost allocation, the main body... Carbon emission responsibility sharing in the alliance It can be represented as:

[0282] (31)

[0283] Define the subject The reduction in carbon emissions resulting from participation in collaboration and their corresponding carbon emission reduction contribution weights Specifically as follows:

[0284] (32)

[0285] In equation (32), as the main body Stepped carbon emission costs when operating independently.

[0286] Furthermore, in S8, an improved Shapley value method considering a carbon emission reduction contribution correction factor is constructed. The traditional Shapley allocation model implicitly assumes that the responsibilities and contributions of each alliance member in environmental protection are absolutely equal, i.e., the contribution weights are all equal. However, due to significant physical differences in the installed capacity of equipment such as gas turbines and electric boilers among the photovoltaic parks participating in the alliance, a main body is defined to eliminate the allocation bias caused by the equalization assumption. The deviation of carbon emission reduction contribution is used as a contribution correction factor, as detailed below:

[0287] (33)

[0288] In equation (33), Contributes a correction factor to carbon emission reduction, when When the target is met, it indicates that the entity has exceeded its emission reduction target and will be rewarded with economic incentives; otherwise, it will be penalized with economic incentives. This serves as the baseline for responsibility.

[0289] (34)

[0290] In equation (34), The alliance is comprised of photovoltaic industrial parks. For shared energy storage.

[0291] Based on the carbon emission reduction contribution correction factor, the initial allocated cost of the entity is calculated. The final total operating cost that needs to be borne as follows:

[0292] (35)

[0293] In equation (35), It serves as a moderating factor for environmental preferences.

[0294] Furthermore, in S9, a benefit alliance consisting of three typical photovoltaic integrated energy parks and a shared energy storage power station is used as the research object to verify the effectiveness of the proposed multi-entity collaborative optimization model. The example includes three parks: Park 1 primarily provides nighttime heating with some daytime source-load misalignment and moderate adjustment capacity; Park 2 is a continuous production park with large energy consumption, gradual load changes, and relatively small adjustment margin, making it a relatively stable energy user within the alliance; Park 3 is a daytime processing park where peak load coincides with peak photovoltaic output, exhibiting good source-load matching and strong demand response capability and dispatch flexibility. In the example, the specific photovoltaic output, load curves, and market price trends of each park are as follows: Figure 2 As shown in Table 4.1, the capacity configuration of each core component is shown in Table 4.1, with the values ​​corresponding to parks 1-3 respectively. The prices for economic and environmental parameters are shown in Table 4.2. This example uses the Cplex solver in MATLAB 2024b to solve the constructed mixed-integer linear programming model.

[0295] Table 1. Configuration of Core Multi-Energy Coupling Equipment and Energy Storage Capacity

[0296]

[0297] Table 2 Price List for Economic and Environmental Parameter Settings

[0298]

[0299] As shown in Table 3, the alliance's net cost before accounting for various revenues was RMB 69,969.28. After deducting the net revenue from spot trading and the revenue from ramp-up services, totaling RMB 52,904.98, the actual total operating cost of the system decreased to RMB 17,064.30. This demonstrates that the alliance not only effectively controls operating expenses through internal optimization and scheduling but also further enhances its overall economic efficiency by leveraging spot market and ramp-up auxiliary service market transactions.

[0300] Table 3. Values ​​of each economic item

[0301]

[0302] Alliance electrical balance such as Figure 3 As shown, during off-peak electricity periods, the alliance achieves inter-temporal energy transfer through electricity purchase and energy storage. During the day, priority is given to consuming photovoltaic power and exporting surplus electricity; during the evening peak, energy supply is ensured through the coordinated output of gas turbines and shared energy storage. The thermal balance and natural gas balance of the park (sections 1-3) are as follows: Figure 4As shown, in terms of heat power balance, the heat load of the three parks exhibits obvious temporal differentiation characteristics due to differences in industry type and energy consumption patterns. Regarding natural gas balance, Park 1 and Park 2 are the main consumers of natural gas within the alliance, with daily gas purchases reaching 4936.87 m³ and 4688.85 m³ respectively. Park 3 has a relatively lower overall gas consumption level, with daily gas purchases of 3602.89 m³, indicating a relatively weaker dependence on external natural gas. Shared energy storage and the results of electricity and heat storage and operation in Parks 1-3 are shown below. Figure 5 As shown, shared energy storage is charged intensively from 01:00 to 05:00 and at noon, and discharged during the morning and evening peak hours, with large fluctuations in SOC to reduce external power purchases; the energy storage in each park participates in load regulation according to its own scale, and the thermal storage is mainly used for balancing the heat load in the morning and evening. Parks 1 and 2 have a greater role, while Park 3 has a smaller overall response amplitude.

[0303] The electricity and heat demand response results for parks 1-3 are as follows: Figure 6 , 7 As shown, the electricity demand response of the three parks all exhibited significant time-period shifting characteristics. Overall, the main periods of load transfer were concentrated between 01:00-05:00, 13:00-16:00, and 23:00-24:00, while the main periods of load transfer out were between 06:00-12:00 and 19:00-22:00. All three parks experienced some load reduction in each period, indicating that the electricity demand response not only achieved time-series load transfer but also effectively reduced the total electricity consumption during peak hours. Regarding heat demand response, Park 1 primarily exhibited cross-period shifting, Park 2 had a relatively continuous heat demand response period distribution, while Park 3 showed a significant segmented and concentrated response characteristic.

[0304] Alliance participation in the market, such as Figure 8 As shown in subgraph (a), the alliance's electricity purchase and sale behavior is highly coordinated with market electricity prices, exhibiting the characteristics of purchasing electricity at low prices and selling it at high prices. Subgraph (b) shows that the alliance has both uphill and downhill ramping capabilities throughout the day, but the contributions of each device differ in their temporal distribution. Shared energy storage demonstrates strong bidirectional adjustment flexibility during ramping, reaching a peak of 5431.58 kW during the uphill period at 02:00, and maintaining a high level during the downhill periods of 10:00-13:00 and 19:00-22:00, fully utilizing its rapid switching characteristics between charging and discharging states.

[0305] Furthermore, in S10, the total revenue of the alliance was allocated using both the traditional Shapley value method and the improved Shapley value method, as shown in Tables 4 and 5. From the traditional Shapley value allocation results, the allocated costs for Park 1, Park 2, Park 3, and the shared energy storage are RMB 7415.00, RMB 13228.72, RMB 7060.99, and -RMB 10640.41, respectively. However, this method fails to reflect the differences in carbon emission reduction contributions among different entities. As shown in Table 5, after introducing carbon emission reduction contribution weights and correction factors, the improved Shapley allocation costs were adjusted to RMB 7473.65, RMB 13372.79, RMB 7155.63, and -RMB 10937.76, respectively, all of which are better than their respective independent operating costs, indicating that the improved allocation results still meet the requirements of individual rationality. The improved method further considers the different contributions of each entity to low-carbon operation on the basis of the traditional Shapley value allocation, so that shared energy storage with higher carbon emission reduction contributions can obtain more revenue allocation.

[0306] Table 4. Cost Table of Participating Entities After Traditional Shapley Value Allocation

[0307]

[0308] Table 5. Cost Table of Participating Entities after Improved Shapley Value Allocation (RMB)

[0309]

[0310] Table 6 compares the cost allocation results for each participating entity under the traditional Shapley value allocation method and the improved Shapley value allocation method. Compared with the traditional method, the improved Shapley value allocation result further adjusts the allocation result for shared energy storage from -10640.41 yuan to -10937.76 yuan, increasing the economic reward by 297.35 yuan, while increasing the economic penalties for the allocated costs of Park 1, Park 2, and Park 3 by 58.65 yuan, 144.04 yuan, and 94.63 yuan, respectively. The proposed improved Shapley value allocation method effectively overcomes the limitation of the lack of environmental responsibility in the traditional allocation model. The allocation result not only reflects the economic contribution of each entity but also objectively measures their actual role in the low-carbon operation of the system.

[0311] Table 6. Cost Table of Participating Entities under Traditional and Improved Shapley Cost Allocation Methods (RMB)

[0312]

[0313] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention. Equivalent transformations or substitutions made based on the above technical solutions all fall within the scope of protection of the claims of the present invention.

Claims

1. A method for coordinated and optimized scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market, characterized in that, The method includes the following steps: S1. Construct an alliance operation framework consisting of multiple photovoltaic parks and shared energy storage power stations. The alliance participates in spot market, natural gas market and flexible ramp-up ancillary service market transactions as a unified market entity. S2. Establish a shared energy storage cyclic aging model, construct a cumulative decay function based on the shared energy storage state of charge, calculate the capacity decay increment caused by charging and discharging, and form a cyclic aging cost model that can be embedded in the optimization scheduling model through piecewise linearization. S3. Establish the objective function of the day-ahead collaborative optimization model, taking into account the net transaction cost of the spot market, gas purchase cost, operation and maintenance cost, demand response cost, aging cost of shared energy storage cycle, tiered carbon trading cost, and ramp-up market revenue; S4. Construct multi-energy balance constraints, equipment operation constraints, callable ramp capacity constraints, and alliance power purchase and sale constraints, which together with the objective function form a complete optimization scheduling model; S5. Establish a marginal contribution calculation framework based on the traditional Shapley value method, enumerate all possible formation orders of the alliance, and calculate the marginal cost contribution brought by each entity when joining the sub-alliance. S6. Weight the marginal contributions of each order according to their probability of occurrence to form the traditional Shapley initial cost allocation scheme, and obtain the initial operating cost to be allocated to each entity; S7. Establish a method for calculating carbon emission reduction contributions, using the tiered carbon trading cost as a characteristic function, and use the Shapley value method to calculate the carbon emission responsibility allocation value of each entity, and then calculate the carbon emission reduction amount and carbon emission reduction contribution weight of each entity compared to independent operation. S8. Construct an improved Shapley value method that considers the carbon emission reduction contribution correction factor. Construct the correction factor based on the deviation between the carbon emission reduction contribution weight and the responsibility baseline, and combine it with the environmental preference adjustment factor to adjust the initial allocation cost with rewards and penalties, forming a final allocation method that takes into account both economic efficiency and carbon emission reduction contribution. S9. Solve the day-ahead collaborative optimization model established by S3 and S4 to obtain the alliance's electricity purchase and sale plan, gas purchase plan, park equipment output, shared energy storage charging and discharging plan, up / down ramp capacity application results, and economic items such as the alliance's total operating cost and tiered carbon trading cost for each time period. S10. Substitute the total cost and tiered carbon trading cost obtained from S9 into the traditional cost allocation scheme established in S5-S6 and the improved cost allocation method established in S7-S8, respectively, to calculate the final cost allocation results for each photovoltaic park and shared energy storage power station, and compare and analyze the two schemes.

2. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, In S1, the alliance's operational framework includes multiple photovoltaic industrial parks and a shared energy storage power station. The alliance participates in day-ahead electricity, natural gas, and flexible ramp-up ancillary services markets as a unified market entity. Each park within the alliance is equipped with a photovoltaic power generation system, along with diverse integrated energy equipment such as gas turbines, gas boilers, electric boilers, power-to-gas converters, and energy and thermal storage systems to meet the various energy needs of the parks, including electricity, heat, and gas. The shared energy storage power station, as an independent flexible adjustment resource within the alliance, is not affiliated with any single park entity. It primarily undertakes power regulation support and shared service functions within the alliance, providing support for the overall operational optimization of the alliance and participation in the flexible ramp-up ancillary services market, as detailed below: S1.1 Operation process, The alliance coordinates the resources of multiple stakeholders internally, optimizing all transaction and operational decisions during the day-ahead phase. Based on price signals and various forecasts, the alliance coordinates decisions regarding electricity and gas purchases, equipment output, shared energy storage charging and discharging, and ramp-up capacity applications. Under the alliance's unified dispatch framework, each park optimizes its operation through adjustments to its own equipment output and coordinated charging and discharging of shared energy storage, fully leveraging the complementary energy consumption characteristics among multiple parks and the flexible adjustment potential of shared energy storage. Simultaneously, the alliance participates in day-ahead electricity and gas market transactions as a unified entity, and, combined with its overall adjustable resource capabilities, completes flexible ramp-up ancillary service market capacity applications. Through this operational mechanism, the alliance achieves coordinated optimization of multi-stakeholder resources and unified decision-making across multiple markets. S1.2 Market Assumptions 1) Market Trading Rules: During the day-ahead phase, the alliance participates in electricity trading and flexible ramp-up ancillary service applications. It arranges its power purchase and sale plans and ramp-up capacity based on day-ahead market prices. As a price taker, the alliance's trading activities do not affect market prices. Within the same dispatch period, the alliance can only choose one method—power purchase or power sale—and cannot engage in both simultaneously. For flexible ramp-up ancillary services, this paper assumes that the alliance's declared upward and downward ramp-up capacity can be fully recognized in the day-ahead market. The corresponding revenue is calculated based on the declared available capacity and capacity price, without considering compensation and performance evaluation factors during actual dispatch. 2) Market Prices and Transaction Boundaries: The day-ahead electricity purchase and sale price, natural gas purchase price, and flexible ramp-up ancillary service capacity price are all considered known parameters. Price fluctuations and the alliance's impact on market prices are not considered. The alliance can engage in electricity purchase and sale transactions with the spot electricity market and purchase natural gas through the external natural gas market. The transaction scale is constrained by the interconnection line transmission capacity and natural gas supply capacity, respectively. The ramp-up capacity declared by the alliance must also meet market declaration limits and equipment operation constraints to ensure the feasibility of the declared capacity. 3) Market entities and cost accounting: The park and shared energy storage form an interest alliance and participate in day-ahead electricity trading, natural gas procurement and flexible ramp-up auxiliary service applications as a unified entity. The revenue and cost of various transactions are calculated based on the day-ahead application results and corresponding prices, without considering intraday deviation assessment, default costs and real-time call compensation. After obtaining the overall optimization results of the alliance, the revenue and cost among the alliance members will be distributed.

3. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, The shared energy storage cycle aging model in S2 includes: To quantify the performance degradation of energy storage batteries during charge-discharge cycles, the instantaneous loss within a time period is first defined. By extracting the difference in cumulative loss states between adjacent time points, the following can be obtained: Battery capacity degradation increment within a given time period: （1） In equation (1), for The increment of capacity decay at any given time; for The state of charge at any given moment; It is a non-linear cumulative decay function, representing the state at a given time. The cumulative wear and tear on the battery, the magnitude of which is on the order of 10. -6 Up to 10 -5 between, Considering the decay function Typically exhibiting a nonlinear characteristic of high at both ends and low in the middle, directly substituting it into the scheduling model can lead to difficulties in solving mixed-integer programming. To improve computational efficiency while maintaining model accuracy, it is divided into... Characterized by linear intervals: （2） In equation (2), This is the starting value of the interval; for In the interval The amount of change within; For interval The attenuation slope reflects the Loss sensitivity of the interval Based on the above attenuation increment, define Cyclic aging cost at any time as follows: （3） In equation (3), This represents the total investment cost of the battery. The unit battery purchase cost is set at 1000 yuan / kWh; The maximum degradation rate at which the battery is scrapped is set to 0.2, meaning that when the actual usable capacity of the battery drops to 80% of the rated capacity, its cycle life is considered to have ended.

4. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S3 includes the objective function for establishing the day-ahead collaborative optimization model: （4） In equation (4), Total operating costs of the alliance; Net transaction costs in the spot market; For gas purchase costs; For operation and maintenance costs; Cost of responding to demand; To share the aging costs of energy storage cycles; For tiered carbon trading costs; To ramp up market profits, (1) Net transaction costs in the spot market, As a participant in the spot market, the consortium engages in electricity purchase and sale transactions with the power grid during various dispatch periods. Therefore, the consortium's net transaction costs in the spot market are expressed as: （5） In equation (5), , They are respectively The power capacity of the Time Alliance for purchasing and selling electricity; , They are respectively Real-time spot electricity market purchase and sale prices (2) Gas purchase cost, All gas turbines and gas boilers in the various parks within the alliance consume natural gas and participate in external natural gas market transactions. Considering that the methane gas generated by the power-to-gas conversion equipment can partially substitute for externally purchased gas, the gas purchase cost is as follows: （6） In equation (6), For the alliance in Constantly purchasing gas volume from the external natural gas market; , , They are respectively Time Park The output electrical power of the gas turbine, the heating power of the gas boiler, and the gas production from methanation; For gas prices; , These are the gas-to-electricity conversion efficiency of the gas turbine and the thermal efficiency of the gas boiler. (3) Operation and maintenance costs, The alliance's operation and maintenance costs mainly include two parts: the operation and maintenance costs of photovoltaic power generation, gas turbines, gas boilers, electric boilers and power-to-gas converters in the park, and the operation and maintenance costs of shared energy storage power stations, as follows: （7） In equation (7), , The respective operation and maintenance costs are for the industrial park and shared energy storage. , They are respectively Time Park The heating power of the electric boiler and the power of the P2G equipment; , They are respectively It can share the charging and discharging power of energy storage at all times; , , , These are the operation and maintenance coefficients for gas turbines, gas-fired boilers, electric boilers, and P2G equipment, respectively. The operation and maintenance coefficient for shared energy storage, (4) Demand response cost, Considering that the park can participate in load regulation through demand response resources, the compensation costs caused by demand response can be included in the total operating cost, as expressed below: （ 8） In equation (8), , They are respectively Time Park The amount of electrical load transfer and reduction; , They are respectively Time Park The amount of heat load transferred or reduced; , These are the transferable and reduceable load factors for electrical loads, respectively. , These are the transferable and reduceable load factors for heat load, respectively. (5) Shared energy storage cycle aging cost, During the internal collaboration between shared energy storage and the park, frequent charging and discharging occur, leading to battery life degradation. To reflect the lifespan loss of shared energy storage during the provision of charging and discharging services, its cycle aging cost is included in the objective function. The cycle aging cost of shared energy storage is expressed as: （9） (6) Tiered carbon trading costs Carbon emissions are primarily considered from the carbon emissions of gas turbines and gas boilers in each industrial park, as well as the carbon emissions from electricity purchased by the consortium in the spot market. System carbon emissions are mainly reduced indirectly by replacing grid-connected electricity with photovoltaic power, and by directly absorbing and converting CO2 using power-to-gas conversion equipment to achieve emission reduction. （10） In equation (10), , They are respectively Carbon emissions and carbon reductions of photovoltaic industrial parks at all times; , , They are respectively Time Park Carbon emissions from purchasing electricity from external power grids, gas turbines, and gas-fired boilers; for Time Park Photovoltaic power output; Carbon emission factor per unit calorific value of natural gas; As a carbon emission factor for electricity, （11） In equation (11), The benchmark carbon trading price; The length of the tiered carbon trading range; For the carbon trading price growth rate, (7) Participation in the climbing market for profit Shared energy storage, due to its rapid charging and discharging characteristics and bidirectional power regulation, possesses a certain ramp-up capability. Furthermore, the gas turbines and electric boilers within the park also have a degree of flexible adjustment capability. Therefore, they can be aggregated to form a callable ramp-up capacity and participate in the ramp-up market. Its revenue is expressed as follows: （12） In equation (12), , They are respectively The Time Alliance can utilize ramp capacity; , These are the unit prices for hill climbing services.

5. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S4 includes basic operational constraints for multi-energy balance, park equipment operation, available ramp-up capacity, alliance power purchase and sale, and shared energy storage: (1) Multi-energy equilibrium constraint 1) Alliance electrical balance constraints The alliance power balance constraint is used to describe the power conservation relationship between photovoltaic power generation equipment, conversion equipment and energy storage equipment, shared energy storage and the power grid in the park. Its expression is: （12） In equation (12), , They are respectively Time Park The charging and discharging power of energy storage devices; , , They are respectively Time Park The base load, transferable load, and load reduction values ​​of the electrical load; , They are respectively Always share the charging and discharging power of the energy storage power station. 2) Thermal balance constraints in the park Considering that thermal energy typically exhibits strong regional locality, thermal balance constraints are established separately for each industrial park. （13） In equation (13), , They are respectively Time Park Thermal power of gas turbines and electric boilers; , They are respectively Time Park The heat absorption and release power of the thermal storage equipment; , , They are respectively Time Park Base load, transferable load, and reduceable load values ​​of heat load. (2) Constraints on the operation of equipment in the park The basic operating constraints of each piece of equipment in the park are as follows: （14） In equation (14), , , , , , These are the upper and lower limits of output for gas turbines, gas boilers, and P2G equipment, respectively. , These are the upper and lower limits of transferable load; This is the upper limit for load reduction; for Time Park Gas turbine start / stop indicator: 1 indicates start-up, 0 indicates shutdown; For the park 0-1 variables that can reduce load Furthermore, considering the mechanical inertia of gas turbines, it is necessary to consider the physical ramp rate constraints between adjacent time periods, as detailed below: （15） In equation (15), , They are respectively Time Park The uphill and downhill ramp rates of the gas turbine. (3) The ramp capacity constraint can be invoked. （16） In equation (16), , They are respectively Time Park Available ramp-up capacity for gas turbines and electric boilers; , Time Park The available downhill ramp capacity of gas turbines and electric boilers; , They are respectively The available uphill and downhill ramp capacity of the shared energy storage is always available. In addition, the alliance's available ramp-up and ramp-down capacity is also subject to market application limits. （17） In equation (17), , These represent the maximum values ​​of the market's declared ramp-up and ramp-down capacity, respectively. 1) Gas turbine Considering the impact of flexible ramping services on available equipment capacity, when gas turbines participate in the ramping market, the reserved upward ramping capacity will reduce the remaining upward ramping capacity of the compressor unit, while the reserved downward ramping capacity will reduce the downward ramping margin of the unit. Therefore, its energy output and ramping reserve capacity must simultaneously meet the constraints of the equipment's operational range, as detailed below: （18） In addition, the uphill and downhill ramp capacity available for the gas turbine must also meet the unit ramp rate limit. （19） 2) Electric boiler Electric boilers are essentially flexible electrical loads. Their ramp-up adjustment direction is opposite to that of power generation equipment. When providing ramp-up capability, electric boilers essentially release electricity by reducing power consumption; when providing ramp-down capability, they absorb more electrical energy by increasing power consumption. Their capacity boundary constraints are as follows: （20） In equation (20), , These are the upper and lower limits of the electric boiler's output; For the thermal efficiency of electric boilers, Furthermore, considering that the participation of electric boilers in the ramp-up market will cause real-time changes in their power consumption and heat production, thus introducing additional disturbances to the thermal system, to ensure the physical feasibility of day-ahead dispatching results even when ramp-up capacity is called up, corresponding thermal regulation capacity needs to be reserved within the system. This capacity will be shared by gas-fired boilers, gas turbines, and thermal storage equipment. When electric boilers provide ramp-up services, their power consumption decreases, and their heat production decreases accordingly, potentially leading to a heat deficit in the system. Therefore, this heat deficit should be compensated by the remaining available additional heating capacity of gas-fired boilers, the increased heating capacity of gas turbines due to increased output, and the heat release capacity of thermal storage equipment. Constraints need to be established on the heat compensation capacity after ramp-up calls to ensure the safe and stable operation of the thermal system. （21） In equation (21), For the thermal efficiency of the gas turbine; for Time Park Heat release indicator for thermal storage equipment; The heat release efficiency of the thermal storage equipment; This refers to the rated capacity of the thermal storage equipment; , They are respectively Time Park The state of charge and lower limit of thermal storage equipment When an electric boiler provides downhill service, it will generate additional heat after increasing its power consumption. To ensure the balance of the thermal system, this additional heat needs to be absorbed through methods such as reducing the heating supply of the gas boiler, simultaneously reducing the heat output of the gas turbine during the downhill process, and absorbing heat through thermal storage equipment. The specific constraints are as follows: （22） In equation (22), for Time Park Heat absorption markings on thermal storage equipment; The heat absorption efficiency of the thermal storage equipment; This represents the upper limit of the state of charge for thermal storage equipment. 3) Shared energy storage When shared energy storage participates in the ramp-up market, its available ramp-up capacity is limited by both the rated charge / discharge power of the equipment and its current operating power, as well as by the energy storage's state of charge. Ramp-up capacity corresponds to the energy storage's ability to increase the system's net injected power, while ramp-down capacity corresponds to the energy storage's ability to decrease the system's net injected power. Therefore, corresponding power boundary constraints must be met, as detailed below: （23） In equation (23), , This represents the maximum value of shared energy storage charging and discharging. Furthermore, considering that ramp-up services typically need to maintain an effective response for a certain period of time, shared energy storage should have sufficient available power when providing ramp-up services and sufficient remaining charging capacity when providing ramp-down services. Based on this, further energy support constraints need to be constructed, as follows: （ 24） In equation (24), , , They are respectively The state of charge of the energy storage power station at any given time and its minimum and maximum values; The rated capacity of the shared energy storage power station; , These are the charging and discharging efficiencies of shared energy storage, respectively. , They are respectively Share the actual maximum ramp capacity of energy storage at all times; , They are respectively Shared energy storage capacity available for ramping up operations at all times. (4) Constraints on the purchase and sale of electricity by the consortium. To prevent the alliance from simultaneously purchasing and selling electricity during the same period, and to ensure that its external transaction power does not exceed the market declaration limit, the following constraints are established for the alliance's electricity purchase and sale: （ 25） In equation (25), , These represent the maximum values ​​for the alliance's external purchases and sales of electricity, respectively. for The 0-1 variable for the Moment Alliance's participation in spot electricity market transactions, when At that time, the alliance purchased electricity from abroad. At that time, the alliance sold electricity to external parties. (5) Basic operational constraints of shared energy storage （26） In equation (26), , These are the charging and discharging flags for the shared energy storage power station, both of which are Boolean variables.

6. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S5 includes enumerating all possible formation orders of the alliance, and deriving the conditions satisfied by the sub-alliances: Assuming the alliance of interests is composed of The alliance consists of several independent decision-making entities, denoted as the complete set of the alliance entities. ,in: (1) Main body For photovoltaic parks participating in the alliance, each entity independently owns the ownership and scheduling decision-making rights of energy equipment such as photovoltaics, gas turbines, and electric boilers within the park, and independently bears the energy demand and operating costs within the park; (2) Main body As the operator of shared energy storage power stations, it independently owns and operates the shared energy storage power stations, and provides power regulation and ramp-up services to the alliance. Any non-empty subset in a consortium Called a sub-alliance, when At that time, the entire alliance was involved. Another cooperative energy supply model studied was a multi-stakeholder issue, where the benefits of each stakeholder in the cooperative project were rationally distributed, i.e., the stakeholder... The revenue equals the mean marginal contribution of the alliance, assuming For the Alliance The minimum total operating cost after participating in market-coordinated operations. The following formula should be satisfied: the total cost of multi-entity collaborative operation should not exceed the sum of the costs of each entity operating independently. （27）。 7. The method for coordinated optimization scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S6 includes the traditional Shapley initial cost allocation scheme: The allocation formula is as follows: （28） In equation (28), These are weighting coefficients, reflecting the sub-alliance The probability of appearing in all alliance combinations; As the main body of the alliance Operating costs allocated using the traditional Shapley value method; The total number of members; For the alliance Number of members; as the main body Pair Alliance Marginal cost contribution Judgment criteria: （29） In equation (29), The total cost for all participating parties, and the sum of the costs shared by all entities within the alliance, equals the minimum total operating cost for the entire alliance to operate collaboratively. （30） In equation (30), as the main body The minimum operating cost for independent market participation is defined as follows: the total cost shared by any entity participating in the alliance is not higher than the total cost of its independent market participation, ensuring that all entities participating in the alliance can achieve cost reduction.

8. The method for coordinated and optimized scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S7 includes a method for calculating carbon emission reduction contributions: To quantify the actual contribution of each entity to the overall low-carbon operation of the alliance, the tiered carbon trading cost is defined as a new characteristic function. It adopts the same marginal accounting logic as economic cost allocation, and the main body Carbon emission responsibility sharing in the alliance It can be represented as: （31） Define the subject The reduction in carbon emissions resulting from participation in collaboration and their corresponding carbon emission reduction contribution weights Specifically as follows: （32） In equation (32), as the main body Stepped carbon emission costs when operating independently.

9. The method for coordinated and optimized scheduling of photovoltaic industrial parks and shared energy storage for a spot-ramp joint market as described in claim 1, characterized in that, S8 includes constructing an improved Shapley value method that considers a correction factor for carbon emission reduction contributions: The traditional Shapley apportionment model implicitly assumes that the responsibilities and contributions of each alliance member in environmental protection are absolutely equal, meaning that the contribution weights are all equal. However, due to significant physical differences in the installed capacity of gas turbines and electric boilers among the photovoltaic parks participating in the alliance, a main body is defined to eliminate the allocation bias caused by the equalization assumption. The deviation of carbon emission reduction contribution is used as a contribution correction factor, as detailed below: （33） In equation (33), Contributes a correction factor to carbon emission reduction, when When the target is met, it indicates that the entity has exceeded its emission reduction target and will be rewarded with economic incentives; otherwise, it will be penalized with economic incentives. As a baseline for responsibility, （34） In equation (34), The alliance is comprised of photovoltaic industrial parks. For shared energy storage, Based on the carbon emission reduction contribution correction factor, the initial allocated cost of the entity is calculated. The final total operating cost that needs to be borne as follows: （35） In equation (35), It serves as a moderating factor for environmental preferences.

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