System and method for calculating annual peak and deep adjustment capability of electric power system in electric power spot market

Abstract

The invention relates to a system and a method for calculating annual peak and deep adjustment capability of a power system in a power spot market, which realize unified evaluation of adjustment capability of a power generation side and a power utilization side through a supply and demand integrated architecture of data input, quotation modeling, market clearing, capacity authentication and result output, and realize accurate evaluation of the adjustment capability of the power generation side and the power utilization side based on refined analysis of 8760 hours in the whole year. And the actual operation characteristics of the power system are accurately reflected. And in combination with fuel, wear, environmental cost and other models, a scientific basis is provided for optimal configuration of electric power resources. And source-load double-side coordinated regulation evaluation is realized, the power utilization side peak load shifting capability is taken into consideration of system flexibility, and the new energy consumption capability and the power grid safety are improved.

Description

Technical Field

[0001] This invention belongs to the field of calculation technology of annual peak and deep adjustment capacity of power system, especially the calculation system and method of annual peak and deep adjustment capacity of power system in the electricity spot market. Background Technology

[0002] During the construction and development of new power systems, the installed capacity of new energy sources will continue to grow. However, due to the intermittent nature of new energy output and grid-unfriendly characteristics such as anti-peak shaving, coupled with the continuous growth of electricity load, challenges are posed to the power system's power balance, safe operation, and supply guarantee. The power system possesses controllable power regulation resources on both the generation and user sides, including the deep regulation capacity of coal-fired power units and the power controllability of certain types of electricity loads. The regulation capabilities of these resources require economic incentives to enable them to spontaneously and proactively provide controlled regulation to the power system.

[0003] The electricity spot market is gradually being developed in various provinces across China. This market generates time-varying electricity prices, and both generators and consumers participating in the market must settle their electricity bills based on the prices determined by the spot market. Because the value of electricity varies at different times, the settlement fees for generators and consumers also differ. Specifically, during high-price periods, generators tend to generate more electricity to obtain higher revenue, while consumers tend to consume less electricity to reduce their expenses. During low-price periods, the behavior of generators and consumers exhibits the opposite characteristics. Therefore, the price in the electricity spot market is a crucial signal for achieving proactive power regulation in generation and consumption. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a system and method for calculating the annual peak and deep-shortage capacity of the power system in the electricity spot market. Considering the trading behavior characteristics of market participants on both the generation and consumption sides, this invention constructs a method for assessing the overall peak and deep-shortage power regulation capacity of the power system. This invention can be applied to the assessment of renewable energy consumption, active power control, and reliability of the power system in a market environment.

[0005] The technical problem solved by this invention is achieved through the following technical solution: The power system's annual peak and deep-shortage capacity calculation system in the electricity spot market includes a login authentication module, a data input module, a bidding modeling module, a market clearing module, a capacity authentication module, and a data output module. These modules are connected sequentially. The login authentication module is used for user identity authentication; The data input module is used to input unit parameters, electricity consumption parameters, grid parameters, and market rules. The pricing modeling module includes generation measurement and load side. The generation measurement is based on the typical quadratic function cost of the unit and the market price limit to generate a monotonically non-decreasing segmented pricing curve. The load side divides the willing-to-pay electricity price into monotonically non-increasing segments to generate the electricity consumption side pricing curve. The two pricing curves are sent to the market clearing module together. On an annual scale, the market clearing module aims to maximize social welfare, taking into account the adjustable demand and rigid load on the generation side. Based on demand, it considers the coupling factors of line quotas and energy storage charging and discharging in multiple time periods, calculates the marginal electricity price at each node, the connection status of each unit, the line congestion status, and the amount of power curtailment and power shortage, and records the set of time periods when the marginal electricity price at each node reaches the upper / lower price limit. The capacity certification module takes the maximum winning bid power of the power generation side within the set of time limits with the upper price limit as the peak capacity, and takes the maximum downward adjustment power as the deep adjustment capacity within the set of time limits with the lower price limit as the benchmark of 50% of the rated power, and determines the qualification based on the daily revenue not being lower than the daily cost; for the electricity consumption side, within the same set of price limits, the maximum reduction amount is taken as the peak shaving capacity based on the actual electricity consumption difference, and the maximum increase in load is taken as the valley filling capacity. The data output module is used to aggregate the qualified peak generation capacity, deep regulation capacity, peak shaving capacity, and valley filling capacity to form the total peak capacity and total deep regulation capacity of the system.

[0006] Furthermore, the unit parameters include rated output, minimum output, stable combustion threshold, oil injection threshold, fuel cost, wear cost, environmental cost, ramping constraints, and start-stop constraints. The power consumption side parameters include non-adjustable power, adjustable power, peak shifting window, peak shifting efficiency, and response rate. The grid parameters include power flow transfer factor and line quota. The market rules include upper and lower price limits, number of price segments, and minimum transaction volume.

[0007] A calculation method for a power system's annual peak and deep-shortage capacity calculation system in the electricity spot market includes the following steps: Step 1: The data input module inputs data into the quotation modeling module, which then constructs a cost and quotation model for coal-fired power units on the power generation side. Step 2: The pricing modeling module constructs a user cost and pricing model for the electricity consumption side; Step 3: The market clearing module performs year-round optimized clearing based on the model built in Steps 1 and 2. Step 4: The capacity verification module (generation side) calculates the peak and deep adjustment capacity of the generation side based on the optimization clearing results and the set of price-limited periods; Step 5: The capacity certification module (electricity consumption side) calculates the peak shaving and valley filling capacity on the electricity consumption side based on the clearing results and the price upper / lower limit set; Step 6: The data output module calculates the total peak and total deep regulation capacity of the system based on the peak shaving and valley filling capacity of the power generation and consumption sides.

[0008] Furthermore, step 1 includes the following steps: Step 1.1: Set the interval Based on the stable combustion and fuel injection thresholds, it is divided into three intervals: Step 1.2: Based on the intervals set in Step 1.1, construct the total cost model: Step 1.3: Calculate the marginal cost based on the constructed total cost model: Step 1.4: Calculate the final price quote curve based on marginal cost. Imposing market price constraints: Step 1.5, Peak Capacity Segment Processing, only takes effect within the peak capacity segment, and serves as a prerequisite correction for Step 1.4.

[0009] Furthermore, step 2 includes the following steps: Step 2.1, Equipment Grouping and Parameter Setting: Step 2.2: Perform segmented modeling based on the grouping results from Step 2.1. Step 2.3, Internal Optimization of the Cost Layer: Using the segmented set (j,t,m) formed in Step 2.2 as the decision-making unit, optimize the electricity price for a given time period. Next, construct the objective function and its constraints, including: peak shifting conservation constraints, ramping constraints, and total power purchase constraints; Step 2.4: Generate a piecewise demand curve based on the objective function in Step 2.3.

[0010] Furthermore, step 3 includes the following steps: Step 3.1, Data reception; Step 3.2: Construct the clearing model and its constraints based on the data received in Step 1: Step 3.3: Solve the clearing model constructed in Step 3.2 throughout the year; Step 3.4: Based on the results obtained in Step 3.3, formulate the price and compliance; Step 3.5: Calculate the transaction volume based on the price and compliance established in Step 3.4.

[0011] Furthermore, step 4 includes the following steps: Step 4.1, Daily Revenue of the Computer Group; Step 4.2, Daily Cost of Computer Group Step 4.3: Based on the unit's daily revenue and daily cost, construct the conditions for inclusion in the capital account; Step 4.4: Based on the eligibility criteria in Step 4.3, define the set of time periods with the daily price ceiling and calculate the peak capacity; Step 4.5: Based on the eligibility criteria in Step 4.3, calculate the deep adjustment capacity using 50% of the rated capacity as a benchmark.

[0012] Furthermore, step 5 includes the following steps: Step 5.1: Calculate peak reduction and valley filling amounts; Step 5.2: Define the price limit time period set; Step 5.3: Calculate the peak shaving capacity based on the price limit period set and peak shaving amount from Step 5.2; Step 5.4: Calculate the filling capacity based on the price limit period set and filling volume from Step 5.2; Step 5.5: Output peak reduction capacity and valley filling capacity.

[0013] Furthermore, step 6 includes the following steps: Step 6.1: Calculate the total peak capacity of the system; Step 6.2: Calculate the total deep tuning capacity of the system; Step 6.3: Output the total peak capacity and total deep tuning capacity of the system.

[0014] The advantages and positive effects of this invention are: 1. This invention models the generation and consumption sides under the same market clearing environment (8760h): the generation side uses a combination of "secondary fuel cost, wear cost, environmental cost, oil injection cost, and high load cost" to form marginal costs; the consumption side uses a monotonic segmentation of "willingness to pay electricity price - electricity volume" and is classified according to "non-adjustable power + adjustable power" to achieve peak shaving and valley filling assessment. Subsequently, a clearing model maximizing social welfare is used to address constraints such as line power flow, unit ramping, energy storage SOC, and load shifting to obtain nodal prices and transaction results. Using "daily revenue ≥ daily cost" as the eligibility threshold, the peak and deep regulation capacity of the generation side and the peak shaving and valley filling capacity of the consumption side are calculated separately, and finally summarized into the system's annual total peak and total deep regulation capacity.

[0015] 2. This invention constructs an integrated supply and demand architecture, linking "data - quotation - clearing - capacity - aggregation" into a whole, avoiding the independent operation of each link.

[0016] 3. The generation-side segmented cost model of this invention adds wear, environmental factors, low-load fuel injection, and high-load additional costs to the traditional fuel secondary term, forming a chain of "segmented cost - marginal cost - segmented pricing". 4. In this invention, the electricity consumption side monotonically segments the "willingness to pay electricity price - electricity consumption" and classifies user electricity consumption behavior into "unadjustable power + adjustable power". The unadjustable portion is quoted at the market ceiling price, while the adjustable portion generates segmented demand curves based on capacity and the highest willingness to pay. Through constraints such as peak shifting windows and response rates, peak shaving and valley filling assessments are achieved on the electricity consumption side.

[0017] 5. This invention determines capacity based on price limits, defines peak generation and deep regulation on the power generation side and peak shaving and valley filling on the power consumption side based on the time period set of "upper price / lower price", and uses "daily revenue ≥ daily cost" as the statistical rule. The process is clear and ensures technical feasibility and economic rationality. Attached Figure Description

[0018] Figure 1 This is a flowchart of the system of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The present invention will be further described in detail below with reference to the accompanying drawings.

[0020] In the electricity spot market, the power system's annual peak and deep-shortage capacity calculation system, such as... Figure 1 As shown, it includes a login authentication module, a data input module, a price modeling module, a market clearing module, a capacity authentication module, and a data output module, which are connected sequentially. The data input module is connected to the login authentication module and is used to input unit parameters (rated output, minimum output, stable combustion threshold, oil injection threshold, fuel cost, wear cost, environmental cost, ramping constraint, start-stop constraint), power consumption side parameters (non-adjustable power, adjustable power, peak shifting window, peak shifting efficiency, response rate), grid parameters (power flow transfer factor and line limit), and market rules (upper and lower price limits, number of price segments, minimum transaction volume).

[0021] The pricing modeling module is connected to the data input module: the pricing modeling module includes generation and load sides. The former generates a monotonically increasing segmented pricing curve based on the typical quadratic function cost of the generating unit and the market price limit; the latter segments the "willingness to pay electricity price - electricity consumption" monotonically without increasing, generating a consumer-side pricing curve; both pricing curves are sent to the market clearing module. On the supply side, cost factors such as fuel secondary items, wear, emissions, low-load fuel injection, and high-load surcharges are integrated. After obtaining the marginal cost, optimization adjustments are made based on upper and lower price limits, monotonicity, and minimum transaction volume, ultimately generating a submittable segmented pricing curve for the generation side. On the consumer side, the "willingness to pay electricity price - electricity consumption" is categorized into adjustable power and non-adjustable power. The non-adjustable power portion is quoted at the market price limit, while the adjustable power portion is quoted according to the corresponding capacity and the highest payable electricity price, thus obtaining the demand curve and reduction curve for the consumer side.

[0022] The market clearing module is connected to the pricing modeling module. On a scale of 8760 hours per year, with the goal of maximizing social welfare, it considers adjustable demand and rigid load on the generation side. Based on demand, and considering factors such as line quotas and the coupling of energy storage charging and discharging in multiple time periods, it calculates the marginal electricity price at each node, the connection status of each unit, the line congestion status, and the amount of power curtailment and shortage. It also records the set of time periods when the marginal electricity price at each node reaches the upper / lower price limit.

[0023] The market clearing module, operating on an annual timescale of 8760 hours, combines segmented supply and demand with rigid loads, considering factors such as line limits, energy storage capacity and power constraints, and generator ramp-up based on actual demand. It employs a mixed-integer programming approach to maximize social welfare.

[0024] The capacity certification module is connected to the market clearing module: On the power generation side, the maximum winning bid power is taken as the peak capacity within the set of periods with the upper price limit, and the maximum downward adjustment power is taken as the deep adjustment capacity within the set of periods with the lower price limit, based on 50% of the rated power, and eligibility is determined by "daily revenue not being lower than daily cost"; On the electricity consumption side, based on the difference between "electricity consumption without price incentives and actual electricity consumption" within the same set of price limits, the maximum reduction amount is taken as the peak shaving capacity, and the maximum increase in load is taken as the valley filling capacity.

[0025] The data output module is connected to the capacity certification module and is used to aggregate the qualified peak generation capacity, deep regulation capacity, peak consumption capacity, and valley filling capacity to form the total peak capacity and total deep regulation capacity of the system.

[0026] A calculation method for a power system's annual peak and deep-shortage capacity calculation system in the electricity spot market, such as... Figure 2 As shown, it includes the following steps: Step 1: The data input module inputs data into the pricing modeling module, which then constructs a cost and pricing model for coal-fired power units on the power generation side. The cost model consists of three components: deep peak shaving (oil-fired / non-oil-fired) cost, baseline minimum output, and quadratic function normal cost and peak capacity segment cost. The pricing model is based on the derivative of the quadratic function model; the minimum output is quoted at the market lower limit price, and the maximum output does not exceed the market upper limit price.

[0027] Step 1.1: Segment the running interval and set a clear interval. Based on the stable combustion and fuel injection thresholds, it is divided into three intervals: First segment (regular peak-shaving segment) No oil was added; The minimum output required to maintain stable combustion without adding oil is the threshold for stable combustion.

[0028] Second section (deep adjustment section without oil injection) : No oil is added, but it is close to the stable combustion limit; The third section (deep oil injection adjustment section) It can partially overlap or connect with the second paragraph, when Add oil to aid combustion. The critical output required to add oil for combustion is the threshold for oil injection.

[0029] Step 1.2: Construction of a Unified Cost Model Total cost It consists of basic costs and additional costs:

[0030] in: Total power generation cost (yuan / hour) Unit output (MW) 1. Basic coal consumption cost:

[0031] Where: a, b, c: coal consumption curve coefficients Coal prices.

[0032] 2. Mechanical wear and tear costs:

[0033] in: Thermal stress coefficient Dimensionless thermal stress factor Variable load wear coefficient Variable load rate, the absolute value indicates that wear occurs during both the rise and fall.

[0034] 3. Environmental costs:

[0035] in: For emissions, The unit price for treating pollutants.

[0036] 4. Oil input cost:

[0037] in: Basic oil input volume : Insufficient output compensation coefficient Oil injection threshold output Fuel price, represented by a piecewise function, only when... Oil injection costs are incurred at that time.

[0038] 5. High load increases costs (≥90%) hour):

[0039] in: High load penalty coefficient, Rated capacity of the unit The high-load threshold, taken in this paper as 90% of the rated capacity, reflects the characteristic of accelerated cost increase under high-load output. When the unit output exceeds 90% of the rated capacity, additional costs will be incurred due to reduced efficiency and increased losses.

[0040] Step 1.3: Marginal Cost Calculation right Differentiate to obtain marginal cost :

[0041]

[0042] in: This is an indicator function; it returns 1 if the condition is met, and 0 otherwise. : The partial derivative of total cost with respect to output.

[0043] The derivatives of each component correspond to the basic cost, wear cost, environmental cost, oil injection cost, etc., reflecting the marginal cost differences in different output ranges (oil injection and non-oil injection; low load, normal load and high load).

[0044] Step 1.4, Final Price Curve right Imposing market price constraints:

[0045] And ensure: Minimum output Corresponding market price ; Maximum output Corresponding market price .

[0046] Step 1.5: Peak Capacity Segment Processing Step 1.1 is further subdivided into peak capacity segments. Its marginal cost includes a capacity premium:

[0047] This represents the capacity scarcity coefficient.

[0048] Step 2: The pricing modeling module constructs a user cost and pricing model for the electricity consumption side. The cost model analyzes user electricity consumption characteristics, classifies equipment, and determines adjustable and non-adjustable power. The pricing model quotes a maximum price for the non-adjustable portion and a price for the adjustable portion based on capacity and the maximum payable electricity fee.

[0049] Step 2.1: Equipment Grouping and Parameter Setting User equipment and electricity consumption behavior are categorized into sets of categories. Time set For each type of equipment during the time period Calibration: Among them: rigid power The unified declaration is the upper limit of the market price; the upper limit of adjustable capacity. The uplink response rate and downlink response rate are respectively Peak shifting window Peak shifting efficiency and time delay penalty .

[0050] Step 2.2, Segmented Modeling For each Discretize the "maximum affordable electricity cost" into a monotonically non-decreasing set of pieces. ,satisfy

[0051] in: This indicates the highest willingness to pay per unit of electricity in that segment. This represents the adjustable capacity of the m-th segment. Let represent the set of quote pairs for user j during time period t.

[0052] Step 2.3, Internal Optimization of Cost Layer Electricity price for a given period The following equation is solved to obtain the optimal timing power consumption, reduction, and peak shifting decisions for the adjustable portion: Objective function:

[0053] in: Cost reduction for user type j in segment m of time period t. Reduce power consumption. Peak shifting time penalty coefficient Peak shift time offset The amount of electricity moved from time period t to time period t+τ Electricity price during time period t Total electricity purchased.

[0054] constraint: Peak shifting conservation constraint

[0055] in: Reduce power consumption. Adjustable capacity limit :from Move to Peak shift amount, User j in Actual electricity consumption during the period Total electricity purchase for the system : Input amount after efficiency correction.

[0056] Climbing constraints

[0057] Total electricity purchase

[0058] Window / Capacity Range: like .

[0059] Step 2.4: Generate segmented demand curves according to Sort by highest to lowest capacity, and add up the capacity. and rigid load As a must-buy segment at the market price ceiling: Demand Curve Prices remain unchanged, and demand remains unchanged. Cut-off curve The amount of reduction when the price is p. For reference, by The conclusion is as follows.

[0060] in: Maximum possible load, by The conclusion is as follows.

[0061] Step 3: The market clearing module performs year-round optimized clearing based on the model built in Steps 1 and 2.

[0062] For each time period The power generation side needs to be submitted in segments. Capacity limit and quotes (The quoted price range must remain non-standard) (Descending order). Electricity consumption side submissions are in segments. Capacity limit and the highest affordable electricity price (The bid sections must be in non-ascending order). Additionally, rigid load data must be collected. Price ceiling and penalties for not supplying electricity Parameters such as network parameters (PTDF) and line parameters can be selectively collected. Rated value.

[0063] Step 3.2: Construction of the clearing model Expressed using piecewise linear programming:

[0064] constraint: Capacity constraints: ;

[0065] Power balance constraints:

[0066] in: : No power supply.

[0067] Unit ramp-up constraints:

[0068] in: This represents the climbing rate.

[0069] Feasibility Insurance:

[0070] in: Allowable load loss rate.

[0071] Network trend constraints:

[0072] Ensure that the power flow in the line does not exceed the thermal stability limit.

[0073] Energy storage SOC constraints:

[0074] in: : Energy storage state of charge during time period t Charge and discharge efficiency, : Charging and discharging power to ensure the conservation of stored energy.

[0075] Demand shifting constraints:

[0076] User side-shift peak capacity must not exceed the reduction amount.

[0077] Step 3.3, Solving in 8760 hours Method 1: Solve independently time-by-time, used for cases where cross-time coupling is not considered.

[0078] Method 2: Solve simultaneously throughout the year, for coupled scenarios including ramp-up, energy storage, and peak shifting.

[0079] Step 3.4: Price Formation and Compliance Single-node price: Power balance dual

[0080] Node-based LMP: Node-balanced duality

[0081] in: Energy components : Dual variables of line constraints The marginal cost of system losses. Loss distribution factor Step 3.5, Settlement of Transaction Volume The transaction volume on the power generation side is settled according to the clearing price at each node. Electricity consumption side transaction volume .

[0082] Step 4: The capacity certification module calculates the peak and deep-adjustment capacity on the generation side based on the optimization and clearing results. Peak capacity is included when daily revenue is greater than or equal to daily cost, and is the winning bid capacity range at the market price when the market price reaches the upper limit. Deep-adjustment capacity is included when daily revenue is greater than or equal to daily cost, and is the difference between 50% of the unit's rated capacity and the actual minimum winning bid output of the units within the set.

[0083] Step 4.1, Daily Revenue of the Computer Group unit On a natural day Income is defined as:

[0084] in: : Electricity price at node n where unit i is located Unit i's output during time period t.

[0085] Step 4.2, Daily Cost of Computer Group unit The daily cost is broken down into the sum of three types of costs:

[0086] in Variable costs of electricity generation

[0087] in: Marginal cost.

[0088] In-depth investigation of additional costs

[0089] in: Deep adjustment of cost coefficients Flexibility Costs

[0090] in: : Ramp-up cost coefficient , Number of start-stop cycles , Cost per start-stop cycle.

[0091] mark , This represents the rated capacity of the unit; start-stop items can be set to zero or treated as equivalent amortization in ED-only scenarios.

[0092] Step 4.3, Qualification Assessment Set daily compensation switch The "1" indicates the existence of a deep adjustment and peak compensation mechanism.

[0093]

[0094] like If the conditions are met, the peak capacity and deep adjustment capacity of the unit for the day will both be recorded as 0.

[0095] Daily profit

[0096] in: Deep adjustment, peak compensation.

[0097] Step 4.4, Peak Capacity Calculation Define the set of time periods for the daily upper limit electricity price for generating units:

[0098] in For tolerance, when and At that time, the peak capacity of the generating units is defined as the maximum value of the actual winning bid power of the generating units within that set:

[0099] like ,but .

[0100] Step 4.5: Deep adjustment capacity calculation Define the set of time periods for the lower limit electricity price of generating units today:

[0101] when and At that time, the deep adjustment capacity of the unit is defined as the difference between 50% of the unit's rated capacity and the actual minimum winning bid output of the units within that set:

[0102] like ,but .

[0103] Step 4.6, Output Results Output for each unit .

[0104] Step 5: The data output module calculates the peak shaving and valley filling capacity on the power consumption side based on the peak generation capacity and deep regulation capacity on the power generation side.

[0105] Step 5.1: Calculation of peak reduction and valley filling amounts Get natural days All time periods The price of nodes Electricity consumption side Reduced trading volume And increase transaction volume If we use a "consumption demand curve", let the electricity consumption benchmark be... The actual electricity consumption was ,but

[0106] Step 5.2, Price Limit Period Set

[0107]

[0108] in: Peak shaving period collection : Gathering during the valley filling period Electricity price at the user's location Tolerance.

[0109] Electricity-side costs

[0110] Step 5.3, Peak Shaving Capacity when At that time, the user Peak-shaving capacity is defined as the maximum reduction in trading volume that occurs simultaneously within a set of time periods when prices reach their upper limits.

[0111] like ,but .

[0112] Step 5.4, Valley Filling Capacity when At that time, the user The valley-filling capacity is defined as the maximum increase in negative trading volume occurring simultaneously within a set of time periods when prices reach their lower limits.

[0113] like ,but .

[0114] Step 5.5: Summary and Output Output by user, aggregate, node, or system-wide dimension. .

[0115] Step 6: The data output module calculates the total peak and total deep regulation capacity of the system based on the peak shaving and valley filling capacity on the power consumption side.

[0116] Step 6.1, Total Peak Capacity of the System

[0117] in: : Qualification marker, 1 for qualified, 0 for unqualified. Peak capacity of unit i Peak-shaving capacity for user j.

[0118] Step 6.2, Total System Deep Tuning Capacity

[0119] in: : Deep adjustment capacity of unit i Valley filling capacity for user j.

[0120] Step 6.3, Output Results Output .

[0121] It should be emphasized that the embodiments described in this invention are illustrative rather than limiting. Therefore, this invention includes, but is not limited to, the embodiments described in the specific implementation. Any other implementations derived by those skilled in the art based on the technical solutions of this invention are also within the scope of protection of this invention.

Claims

1. A system for calculating the annual peak and deep-shortage capacity of the power system in the electricity spot market, characterized in that: It includes a login authentication module, a data input module, a pricing modeling module, a market clearing module, a capacity authentication module, and a data output module, which are connected sequentially. The login authentication module is used for user identity authentication; The data input module is used to input unit parameters, electricity consumption parameters, grid parameters, and market rules. The pricing modeling module includes generation measurement and load side. The generation measurement is based on the typical quadratic function cost of the unit and the market price limit to generate a monotonically non-decreasing segmented pricing curve. The load side divides the willing-to-pay electricity price into monotonically non-increasing segments to generate the electricity consumption side pricing curve. The two pricing curves are sent to the market clearing module together. On an annual scale, the market clearing module aims to maximize social welfare, taking into account the adjustable demand and rigid load on the generation side. Based on demand, it considers the coupling factors of line quotas and energy storage charging and discharging in multiple time periods, calculates the marginal electricity price at each node, the connection status of each unit, the line congestion status, and the amount of power curtailment and power shortage, and records the set of time periods when the marginal electricity price at each node reaches the upper / lower price limit. The capacity certification module takes the maximum winning bid power of the power generation side within the set of time limits with the upper price limit as the peak capacity, and takes the maximum downward adjustment power as the deep adjustment capacity within the set of time limits with the lower price limit as the benchmark of 50% of the rated power, and determines the qualification based on the daily revenue not being lower than the daily cost; for the electricity consumption side, within the same set of price limits, the maximum reduction amount is taken as the peak shaving capacity based on the actual electricity consumption difference, and the maximum increase in load is taken as the valley filling capacity. The data output module is used to aggregate the qualified peak generation capacity, deep regulation capacity, peak consumption capacity, and valley filling capacity to form the total peak capacity and total deep regulation capacity of the system.

2. The power system annual peak and deep-shortage capacity calculation system in the electricity spot market according to claim 1, characterized in that: The unit parameters include rated output, minimum output, stable combustion threshold, oil injection threshold, fuel cost, wear cost, environmental cost, ramping constraints, and start-stop constraints. The power consumption side parameters include non-adjustable power, adjustable power, peak shifting window, peak shifting efficiency, and response rate. The grid parameters include power flow transfer factor and line quota. The market rules include upper and lower price limits, number of price segments, and minimum transaction volume.

3. A calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market as described in any one of claims 1 to 2, characterized in that: Includes the following steps: Step 1: The data input module inputs data into the quotation modeling module, which then constructs a cost and quotation model for coal-fired power units on the power generation side. Step 2: The pricing modeling module constructs a user cost and pricing model for the electricity consumption side; Step 3: The market clearing module performs year-round optimized clearing based on the model built in Steps 1 and 2. Step 4: The capacity certification module calculates the peak and deep adjustment capacity on the generation side based on the optimized clearing results and the set of price-limited periods; Step 5: The capacity certification module calculates the peak shaving and valley filling capacity on the electricity consumption side based on the clearing results and the price upper / lower limit set; Step 6: The data output module calculates the total peak and total deep regulation capacity of the system based on the peak shaving and valley filling capacity of the power generation and consumption sides.

4. The calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 1 includes the following steps: Step 1.1: Set the interval Based on the stable combustion and fuel injection thresholds, it is divided into three intervals: Step 1.2: Based on the intervals set in Step 1.1, construct the total cost model: Step 1.3: Calculate the marginal cost based on the constructed total cost model: Step 1.4: Calculate the final price quote curve based on marginal cost. Imposing market price constraints: Step 1.5, Peak Capacity Segment Processing, only takes effect within the peak capacity segment, and serves as a prerequisite correction for Step 1.

4.

5. The calculation method for the annual peak and deep-shifting capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 2 includes the following steps: Step 2.1, Equipment Grouping and Parameter Setting: Step 2.2: Perform segmented modeling based on the grouping results from Step 2.

1. Step 2.3, Internal Optimization of the Cost Layer: Using the segmented set (j,t,m) formed in Step 2.2 as the decision-making unit, optimize the electricity price for a given time period. Next, construct the objective function and its constraints, including: peak shifting conservation constraints, ramping constraints, and total power purchase constraints; Step 2.4: Generate a piecewise demand curve based on the objective function in Step 2.

3.

6. The calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 3 includes the following steps: Step 3.1, Data reception; Step 3.2: Construct the clearing model and its constraints based on the data received in Step 1: Step 3.3: Solve the clearing model constructed in Step 3.2 throughout the year; Step 3.4: Based on the results obtained in Step 3.3, formulate the price and compliance; Step 3.5: Calculate the transaction volume based on the price and compliance established in Step 3.

4.

7. The calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 4 includes the following steps: Step 4.1, Daily Revenue of the Computer Group; Step 4.2, Daily cost of the computer group; Step 4.3: Based on the unit's daily revenue and daily cost, construct the conditions for inclusion in the capital account; Step 4.4: Based on the eligibility criteria in Step 4.3, define the set of time periods with the daily price ceiling and calculate the peak capacity; Step 4.5: Based on the eligibility criteria in Step 4.3, calculate the deep adjustment capacity using 50% of the rated capacity as a benchmark.

8. The calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 5 includes the following steps: Step 5.1: Calculate peak reduction and valley filling amounts; Step 5.2: Define the price limit time period set; Step 5.3: Calculate the peak shaving capacity based on the price limit period set and peak shaving amount from Step 5.2; Step 5.4: Calculate the filling capacity based on the price limit period set and filling volume from Step 5.2; Step 5.5: Output peak reduction capacity and valley filling capacity.

9. The calculation method for the annual peak and deep-shortage capacity calculation system of the power system in the electricity spot market according to claim 3, characterized in that: Step 6 includes the following steps: Step 6.1: Calculate the total peak capacity of the system; Step 6.2: Calculate the total deep tuning capacity of the system; Step 6.3: Output the total peak capacity and total deep tuning capacity of the system.

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