A method, device, equipment and medium for calculating the cost of low-carbon transformation of a power system

Abstract

The application discloses a kind of electric power system low-carbon transformation cost measurement method, device, equipment and medium, it is related to electric power system low-carbon transformation field, the method includes: constructing including objective function and constraint condition low-carbon transformation cost measurement model;Objective function is constructed according to thermal power generating unit operating cost, new energy unit operating cost and thermal power generating unit auxiliary service cost;Constraint condition includes: power balance constraint, thermal power generating unit constraint, new energy unit constraint and new energy system safety and stability constraint;The unit operating state of current time is input into low-carbon transformation cost measurement model and is solved, obtains the optimal solution under different new energy penetration rate of current time;The optimal solution under different new energy penetration rate of current time is respectively input into objective function, and the objective function value obtained under each new energy penetration rate is determined as the low-carbon transformation cost under corresponding new energy penetration rate, the application can accurately realize the measurement of electric power system low-carbon transformation cost.

Description

Technical Field

[0001] This application relates to the field of low-carbon transformation of power systems, and in particular to a method, apparatus, equipment and medium for calculating the cost of low-carbon transformation of power systems. Background Technology

[0002] With the ongoing construction of low-carbon transformation of the new power system, new energy sources will be integrated into the grid on a high proportion and on a large scale. As new energy sources are developed and connected to the grid on a large scale, the volatility and intermittency of photovoltaic and wind power pose significant challenges to the safe and stable operation of the power system, causing it to exhibit strong fluctuations and weak inertia. To ensure the safe and stable operation of the system, more flexible resources are needed, which leads to an increase in the overall system cost of the power system.

[0003] Currently, the cost of renewable energy does not consider the additional costs associated with grid connection; it focuses solely on the cost of renewable energy generation itself. While reflecting the green value of renewable energy generation, it neglects the low-carbon transition costs brought about by the system's development of renewable energy. Furthermore, the relevant electricity market system and subsidy mechanisms cannot accurately measure the cost of renewable energy generation. There is a lack of accurate calculation of the system cost increase resulting from a high proportion of renewable energy integration, and the system cannot accurately assess the cost changes caused by different power generation technologies due to output characteristics and other factors, nor effectively reflect the true cost of renewable energy generation. This is detrimental to incentivizing the sustainable development of renewable energy. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, equipment and medium for calculating the cost of low-carbon transformation of power systems, which can accurately calculate the cost of low-carbon transformation of power systems, steadily and orderly promote the low-carbon transformation of power systems, and encourage the sustainable development of new energy.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] Firstly, this application provides a method for calculating the cost of low-carbon transition in power systems, including:

[0007] To obtain the current operating status of the power system units; the power system includes: thermal power units and new energy units;

[0008] A cost calculation model for low-carbon transformation is constructed. The low-carbon transformation cost calculation model includes an objective function and constraints. The objective function is constructed based on the operating costs of thermal power units, the operating costs of new energy units, and the auxiliary service costs of thermal power units. The constraints include: power balance constraints, thermal power unit constraints, new energy unit constraints, and new energy system safety and stability constraints.

[0009] The current operating status of the generating units is input into the low-carbon transformation cost calculation model for solution, and the optimal solution under different new energy penetration rates at the current moment is obtained. The optimal solution includes: the switching status of each generating unit in the power system and the output of each generating unit when the objective function is minimized.

[0010] The optimal solutions for different new energy penetration rates at the current time are input into the objective function, and the obtained objective function values ​​for each new energy penetration rate are determined as the low-carbon transformation cost for the corresponding new energy penetration rate.

[0011] Secondly, this application provides a cost calculation device for the low-carbon transition of power systems, comprising:

[0012] The data acquisition module is used to acquire the current operating status of the power system units; the power system includes: thermal power units and new energy units;

[0013] The calculation model construction module is used to construct a low-carbon transition cost calculation model. The low-carbon transition cost calculation model includes an objective function and constraints. The objective function is constructed based on the operating costs of thermal power units, the operating costs of new energy units, and the auxiliary service costs of thermal power units. The constraints include: power balance constraints, thermal power unit constraints, new energy unit constraints, and new energy system safety and stability constraints.

[0014] The solution module is used to input the current unit operating status into the low-carbon transformation cost calculation model for solution, and obtain the optimal solution under different new energy penetration rates at the current time; the optimal solution includes: the switching status of each unit in the power system and the output of each unit when the objective function is minimized;

[0015] The low-carbon transition cost determination module is used to input the optimal solutions under different new energy penetration rates at the current moment into the objective function, and determine the obtained objective function values ​​under each new energy penetration rate as the low-carbon transition cost under the corresponding new energy penetration rate.

[0016] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the power system low-carbon transformation cost calculation method described in any one of the above-mentioned methods.

[0017] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the power system low-carbon transition cost calculation method described above.

[0018] According to the specific embodiments provided in this application, this application has the following technical effects:

[0019] This application provides a method, apparatus, equipment, and medium for calculating the cost of low-carbon transformation of power systems. An objective function is constructed based on the operating costs of thermal power units, the operating costs of renewable energy units, and the ancillary service costs of thermal power units. Constraints are established considering power balance constraints, thermal power unit constraints, renewable energy unit constraints, and the safety and stability constraints of the renewable energy system. This determines the low-carbon transformation cost calculation model, enabling the calculation of low-carbon transformation costs under different renewable energy penetration rates. This application considers operating costs, ancillary service costs, the operating characteristics of renewable energy units, and the safety and stability operating conditions of the renewable energy system, making it more suitable for new power systems with a high proportion of renewable energy integration. It accurately calculates the cost of low-carbon transformation of power systems, enabling the steady and orderly promotion of low-carbon transformation of power systems and encouraging the sustainable development of renewable energy. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is an application environment diagram of a method for calculating the cost of low-carbon transformation of a power system according to an embodiment of this application;

[0022] Figure 2 A flowchart illustrating a method for calculating the cost of low-carbon transformation of a power system, provided as an embodiment of this application;

[0023] Figure 3 A schematic diagram of the overall process of the power system low-carbon transformation cost calculation method provided in an embodiment of this application during actual application.

[0024] Figure 4 This is a schematic diagram of a long-cycle calculation process provided in an embodiment of this application;

[0025] Figure 5 A functional module schematic diagram of a power system low-carbon transformation cost calculation device provided in another embodiment of this application;

[0026] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] The cost calculation method for low-carbon transformation of power systems provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on other servers. Terminal 102 can send the current operating status of the power system's generating units to server 104. After receiving the current operating status, server 104 constructs a low-carbon transition cost calculation model for that status. It then inputs the current operating status into the low-carbon transition cost calculation model to solve for the optimal solution under different new energy penetration rates. The optimal solutions under different new energy penetration rates are then input into the objective function, and the obtained objective function values ​​for each new energy penetration rate are determined as the low-carbon transition cost for that corresponding new energy penetration rate. Server 104 can then feed back the obtained low-carbon transition costs for different new energy penetration rates to terminal 102.

[0030] In addition, in some embodiments, the method for calculating the cost of low-carbon transformation of the power system can also be implemented by the server 104 or the terminal 102 separately. For example, the terminal 102 can directly process the unit operating status of the power system at the current moment, or the server 104 can obtain the unit operating status of the power system at the current moment from the data storage system and process the unit operating status of the power system at the current moment.

[0031] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster composed of multiple servers, or it can be a cloud server.

[0032] In one exemplary embodiment, such as Figure 2 As shown, a method for calculating the cost of low-carbon transformation of power systems is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 201 to 204. Wherein:

[0033] Step 201: Obtain the unit operating status of the power system at the current moment; the power system includes: thermal power units and new energy units.

[0034] Step 202: Construct a low-carbon transition cost calculation model; the low-carbon transition cost calculation model includes an objective function and constraints.

[0035] The objective function is constructed based on the operating costs of thermal power units, the operating costs of new energy units, and the ancillary service costs of thermal power units; the constraints include: power balance constraints, thermal power unit constraints, new energy unit constraints, and new energy system safety and stability constraints.

[0036] Step 203: Input the current unit operating status into the low-carbon transformation cost calculation model for solution to obtain the optimal solution under different new energy penetration rates at the current moment.

[0037] The optimal solution includes the switching state of each unit in the power system and the output of each unit when the objective function is minimized.

[0038] Step 204: Input the optimal solutions for different new energy penetration rates at the current time into the objective function respectively, and determine the obtained objective function values ​​for each new energy penetration rate as the low-carbon transformation cost for the corresponding new energy penetration rate.

[0039] Implementing steps 201 to 204 above can accurately calculate the cost of the low-carbon transformation of the power system, steadily and orderly promote the low-carbon transformation of the power system, and encourage the sustainable development of new energy sources.

[0040] In another exemplary embodiment of this application, please refer to Figure 1 Following step 204, the method for calculating the cost of low-carbon transformation of the power system further includes:

[0041] Step 205: Calculate the difference in low-carbon transition costs under different new energy penetration rates to obtain the corresponding cost increment.

[0042] In another exemplary embodiment of this application, the expression of the objective function is:

[0043] Min F = F1 + F2;

[0044] Where F represents the objective function; F1 represents the combined power generation cost of the power system; and F2 represents the cost of ancillary services provided by thermal power units.

[0045] The expression for the combined generation cost of power units in a power system is:

[0046]

[0047] Where f1 represents the operating cost of a thermal power unit; f2 represents the operating cost of a wind power unit; f3 represents the operating cost of a photovoltaic unit; N G M represents the number of thermal power units; N represents the number of time periods; T Indicates the number of moments; P represents the electricity price quoted by thermal power unit i at time t in time period m; i,m,t This represents the output of thermal power unit i at time t during the time period m; This represents the startup cost of thermal power unit i; This represents the downtime cost of thermal power unit i; This represents the no-load operating cost of thermal power unit i; v i,t This represents the start-up action of thermal power unit i at time t, and is a 0-1 variable, where 1 represents start-up and 0 represents other actions; w i,t This represents the shutdown action of thermal power unit i at time t, and is a 0-1 variable, where 1 represents shutdown and 0 represents other actions; u i,t This indicates whether thermal power unit i is in no-load operation at time t, and is a 0-1 variable, where 1 indicates operation and 0 indicates disconnection from the grid; N W Indicates the number of wind turbine units; N PV Indicates the number of photovoltaic units; This indicates the price quote for wind turbine unit j; P represents the price quote for photovoltaic unit k; j,t P represents the output power of wind turbine j at time t; k,t This represents the output power of photovoltaic unit k at time t.

[0048] The expression for the cost of ancillary services provided by thermal power units is:

[0049]

[0050] Where f4 represents the cost of providing upper and lower reserves for thermal power units; f5 represents the cost of providing deep peak-shaving ancillary services for thermal power units; f6 represents the cost of providing primary and secondary frequency regulation for thermal power units; N T N represents the number of moments; G Indicates the number of thermal power units; This indicates the standby quote for thermal power unit i at time t; P represents the standby quote for thermal power unit i at time t; i ur P represents the reserve power provided by thermal power unit i; i dr This indicates the lower reserve power provided by thermal power unit i; This indicates the price quote for deep peak shaving of thermal power units; P i dp Indicates the peak-shaving capacity of thermal power unit i; This represents the price per mileage of a thermal power unit i at time t during primary frequency regulation. This represents the secondary frequency regulation mileage price of thermal power unit i at time t; This represents the primary frequency regulation capacity price of thermal power unit i at time t; This represents the secondary frequency regulation capacity price of thermal power unit i at time t; This represents the primary frequency regulation performance index of thermal power unit i at time t; This represents the secondary frequency regulation performance index of thermal power unit i at time t; This represents the first frequency regulation capacity of thermal power unit i at time t; This represents the secondary frequency regulation capacity of thermal power unit i at time t.

[0051] In another exemplary embodiment of this application, the power balance constraint and thermal power unit constraint in the constraints are treated as conventional constraints. The thermal power unit constraints include: thermal power unit ramping constraint and thermal power unit start-up and shutdown time constraint. The new energy unit constraints include: wind power output constraint, photovoltaic power output constraint, and new energy absorption rate constraint. The new energy system safety and stability constraints include: frequency stability constraint, upper and lower reserve constraints, power flow safety constraints, node constraints, and system minimum inertia constraint.

[0052] The following section provides a detailed explanation of each constraint.

[0053] (1) Conventional constraints

[0054] 1) Power balance constraints.

[0055] The output of both new energy generating units and conventional generating units (thermal power units) is equal to the load size. The system power needs to remain balanced at every moment. The power balance constraint is described as follows:

[0056]

[0057] Among them, P i,t N represents the output power of thermal power unit i at time t; L Indicates the number of load nodes; P d,t This represents the output power of load node d at time t.

[0058] 2) Slope climbing constraints for thermal power units.

[0059] The unit ramp-up constraint refers to the requirement that the output change of the unit between two adjacent time periods must be within its allowable ramp-up range, i.e.:

[0060]

[0061] in, Indicates the unit's ramp-up rate; R P represents the rate of rate of climb for the generator unit. i,t-1 This represents the output power of thermal power unit i at time t-1.

[0062] Furthermore, when the minimum starting power of a thermal power unit exceeds the ramp rate, the ramp constraint will prevent all shut-down thermal power units from starting. Therefore, the ramp constraint for thermal power units is rewritten as follows:

[0063]

[0064] in, S i This indicates the maximum output reduction when thermal power unit i is shut down; This indicates the maximum lifting force of thermal power unit i during startup; R i This represents the downhill ramp rate of thermal power unit i; Indicates the rate of ascent of thermal power unit i; u i,t-1 This indicates whether thermal power unit i is in no-load operation at time t-1.

[0065] In addition, to simplify the calculation, both the maximum startup rate of increase and the maximum shutdown rate of decrease can be set to:

[0066]

[0067] 3) Start-up and shutdown time constraints for thermal power units.

[0068] When a thermal power unit is started up, it must be guaranteed to run for a period of time, during which it can only be started up once; similarly, when a thermal power unit is shut down, it must also be guaranteed to stop running for a period of time (minimum shutdown time), which can be described as:

[0069]

[0070] Among them, TU i Indicates the minimum start-up time of thermal power unit i; TD i Indicates the minimum shutdown time of thermal power unit i; v i,a This indicates the start-up action of thermal power unit i at time a, where 1 indicates start-up and 0 indicates other actions; w i,a This indicates the shutdown action of thermal power unit i at time a, where 1 represents shutdown and 0 represents other actions.

[0071] The three Boolean variables have the following relationship, which can be understood as: a unit that has been started can only be shut down, and a unit that has been shut down can only be started. This can be described as:

[0072] u i,t -u i,t-1 =v i,t -w i,t ;

[0073] The above three formulas represent the start-up and shutdown time constraints of thermal power units.

[0074] (2) Constraints on new energy units.

[0075] 1) Wind power output constraints are:

[0076] 0 < P W,t <P W,t,Max ;

[0077] Among them, P W,t P represents the wind farm output at time t. W,t,Max This indicates the predicted maximum output of the wind farm at time t.

[0078] 2) Photovoltaic output constraints are:

[0079] 0 < P PV,t <P PV,t,Max ;

[0080] P PV,t P represents the output of the photovoltaic field at time t. PV,t,Max The value represents the predicted maximum output of the photovoltaic field at time t.

[0081] 3) The constraint on the renewable energy consumption rate is:

[0082]

[0083] In the formula, N G,w N represents the actual number of wind turbine units. G,pv Indicates the actual number of photovoltaic units; This represents the actual output of wind turbine j at time t; This represents the actual output of photovoltaic unit k at time t; This represents the actual maximum possible output of wind turbine j at time t; represents the actual maximum possible output of photovoltaic unit k at time t; h1 and h2 are the minimum renewable energy absorption rates of wind turbine and photovoltaic unit, respectively.

[0084] (3) Safety and stability constraints of new energy systems.

[0085] 1) Frequency stability constraints.

[0086] To ensure the frequency safety of the system, after disturbances occur on the renewable energy and load sides, the frequency rise or fall must remain within the system's tolerable safe range. Therefore, the frequency stability constraints can be constructed as follows:

[0087] f a ≤f N +Δf≤f b ;

[0088] f a This represents the lower limit of the frequency, typically set as the lower limit of the system frequency; f b This represents the upper limit of the frequency, typically set to the system frequency limit; f N Δf represents the frequency reference value; Δf represents the frequency change value.

[0089]

[0090] Wherein, ΔP NE ΔP represents the active power fluctuation caused by new energy generating units. L K represents the active power fluctuation caused by the load. G This represents the static characteristic coefficient of the generator set's power frequency.

[0091] 2) Upper and lower spare constraints.

[0092] As uncertainties on both the source and load sides of high-proportion renewable energy systems increase, fluctuations on either side can cause power imbalances. This application will consider the system's reserve constraints from both the generation and load sides.

[0093] On the one hand, due to the volatility and uncertainty of wind and solar power output, these fluctuations can cause disturbances in the power system. Therefore, the system needs to reserve spinning reserves to cope with the uncertainties caused by these two factors. On the other hand, to address the uncertainties caused by load forecast deviations and load fluctuations on the load side, and to avoid their impact on power quality, the system typically also has a certain reserve to smooth out this portion of unbalanced power, thereby ensuring the safe and stable operation of the system. The system's upper and lower reserve requirements are first determined using the following formulas:

[0094]

[0095] Among them, R t U R t D These represent the system's upward and downward adjustments to reserve requirements at time t, respectively; κ t U κ t DThese represent the upward and downward adjustment of the reserve demand coefficients at time t, respectively, determined based on the predicted fluctuations of renewable energy units and uncontrollable loads in each time period. When the proportion of fluctuating loads and renewable energy units is relatively large, the upward and downward reserve demand coefficients are correspondingly larger; δ d D δ represents the standard deviation of uncontrollable load power. j W Indicates the standard deviation of wind turbine output; δ i S This represents the standard deviation of a photovoltaic unit.

[0096] In addition to considering the volatility of new energy sources and load side, the situation where conventional thermal power units are taken out of operation due to failure should also be considered, and corresponding reserve capacity should be reserved, using R i G,Max R represents the output of the largest thermal power unit in the system at maximum load. i G,Min This represents the maximum capacity unit output in the system at minimum load. Therefore, the system's reserve / standby requirements can be expressed as:

[0097] R up =Max{R t U ,R i G,Max};

[0098] R dn =Max{R t D ,R i G,Min};

[0099] Therefore, the upper standby constraint for establishing the model is:

[0100]

[0101] The following standby constraint is:

[0102]

[0103] R up R is the system's backup requirement. dn This is the system's backup capacity requirement; This represents the maximum output power of thermal power unit i; P i This represents the minimum output power of thermal power unit i.

[0104] 3) Current safety constraints.

[0105] Transmission line power flow constraints refer to the requirement that the power flow on the line should be less than the allowable limit of the power flow on the line. Currently, the most widely used method is to use the DC power flow model to solve the power flow on the line. The specific model is as follows:

[0106]

[0107] In the formula, θ(s,t) represents the phase angle of bus s at time t; K(l,s) represents the relationship between transmission line l and bus s, taking values ​​of 1, -1, and 0; x l Indicates the reactance parameters of the transmission line; P l P represents the maximum and minimum power of line l; l,t This represents the output power of line l at time t.

[0108] After calculating the power flow transfer distribution factor matrix G, the power flow safety constraints are rewritten as follows:

[0109]

[0110] Among them, G l-i This represents the effect of power injection at node i on line l; G l-d This indicates the effect of power injection at node d on line l.

[0111] 4) Node constraints.

[0112] Node constraints include node power balance constraints and node voltage constraints.

[0113] The nodal power balance constraint means that at any node in a power system, the injected power is equal to the outflow power at any given time, i.e.:

[0114]

[0115] Where I represents the total number of generator sets in the system; K p,n,t Represents the elements of the node-generator correlation matrix; P nm,t D represents the power flow of line nm at time t; n,t This represents the load of node n at time t.

[0116] Node voltage constraints:

[0117] V min,n ≤V n ≤V Max,n ;

[0118] V n V represents the voltage magnitude at node n. Max,n V represents the maximum voltage at node n; min,n This represents the minimum voltage at node n.

[0119] 5) System minimum inertia constraint.

[0120] With the large-scale development and utilization of centralized and distributed wind power and photovoltaics, the proportion of synchronous generators in the system is gradually decreasing, while the penetration rate of new energy sources is gradually increasing. This leads to a decrease in the system's equivalent inertia level, threatening and challenging the system's frequency stability. The system inertia must meet the minimum inertia requirement, i.e., the system's minimum inertia constraint is:

[0121] M s +M w +M PV +M e ≥M min ;

[0122] M s M represents the system inertia provided by the synchronous generator. w M represents the virtual system inertia provided by the wind turbine. PV M represents the virtual inertia provided by the photovoltaic unit. e This represents the virtual inertia provided by energy storage. Minimum inertia M min It can be determined by two indicators: the rate of change of frequency and the frequency offset, expressed as:

[0123] M min =Max{M min,RoCoF M min，nadir};

[0124] M min,RoCoF M represents the minimum demand inertia considering the rate of change of frequency constraints. min，nadir This represents the minimum required inertia considering the constraint of the lowest frequency point.

[0125] In another exemplary embodiment of this application, if it is to calculate the low-carbon transition cost and cost increment for a short period (at various times of a day or at a certain time), then by performing the above steps 201 to 205 for each time, the low-carbon transition cost and cost increment under different new energy penetration rates in the short period can be obtained.

[0126] To calculate the costs and cost increments of low-carbon transition over a long period (a year or even longer), steps 201 to 205 above should be performed, using the unit operating status at the end of the previous day as the starting point of the next day. This daily rolling calculation will yield the low-carbon transition costs and cost increments under different renewable energy penetration rates over the long term. In other words, the calculation of long-term low-carbon transition costs and cost increments must satisfy the condition that if the current time is the starting point of the day, the unit operating status at the end of the previous day should be used as the current unit operating status.

[0127] Combination Figure 3 The overall process of this embodiment in actual application can be specifically described as follows:

[0128] (1) Construct an intraday low-carbon transition cost calculation model, that is, realize the low-carbon transition cost calculation for short-cycle prediction.

[0129] The low-carbon transition cost calculation model includes an objective function and constraints. The objective function consists of two parts: the combined power generation cost F1 and the ancillary service cost F2 provided by thermal power units. This allows us to calculate the minimum operating cost of the system under different renewable energy penetration rates, i.e., the value of the objective function. The specific expression of the objective function will not be elaborated here. The constraints include: power balance constraints, thermal power unit constraints, renewable energy unit constraints, and renewable energy system safety and stability constraints. The specific expressions for each constraint will not be elaborated here.

[0130] (2) Construct a long-term low-carbon transition cost calculation model, that is, realize long-term prediction of low-carbon transition cost calculation.

[0131] Considering the continuity and stability of production plans, this application further constructs a long-cycle low-carbon transition cost calculation model to calculate the system's low-carbon transition costs over a period of one year or even longer, optimizing resource allocation over a longer timeframe and more comprehensively considering cost changes brought about by the development of new energy sources. Its core remains the aforementioned low-carbon transition cost calculation model. The specific solution approach is as follows: the long-cycle production cost simulation model is decomposed into multiple sub-models based on the time scale. Within each simulation cycle, a 36-hour unit combination is solved, and the output results are only read from the first 24 hours. Then, the unit status calculated in the 24th hour is used as the initial value for the simulation calculation of the next 36 hours, and so on, with daily rolling calculations. The long-cycle calculation satisfies the following formula:

[0132]

[0133] Where day represents the long-term calculation period, in days; u i day-1,24 This indicates the operating status of thermal power unit i in the 24th hour of the previous day; u i day,0 This indicates the initial operating status of thermal power unit i one day later.

[0134] Long-term calculation process as follows Figure 4 As shown.

[0135] This application comprehensively considers multi-dimensional boundary conditions such as power structure, grid parameters, and renewable energy penetration rate. It introduces renewable energy constraints and renewable energy system safety operation constraints into the Security Constrained Unit Commitment (SCUC) model to obtain a low-carbon transition cost calculation model. It calculates the low-carbon transition cost under different renewable energy penetration rates, effectively measures the additional impact of renewable energy grid connection, and makes a relatively accurate calculation of the incremental cost of low-carbon transition brought about by a high proportion of renewable energy access.

[0136] Building upon this foundation, a long-term low-carbon transition cost calculation model was further constructed. This model uses the unit operating status of the previous day's 24th hour as the initial operating status for the next day, and calculates the low-carbon transition cost over a longer timescale on a rolling basis. Through the established model, various renewable energy penetration rate scenarios were set up to obtain the system's low-carbon transition cost and cost increment under different renewable energy penetration rates. This provides data reference for the power system's low-carbon transition, measures the additional economic impact of renewable energy development at different penetration rates, and steadily promotes the construction process of the power system's low-carbon transition.

[0137] The power system low-carbon transition cost calculation method described in the above embodiments has the following advantages:

[0138] (1) Starting from the traditional SCUC unit combination model, this application incorporates new energy constraints and new energy system safety operation constraints into the SCUC model, establishing a low-carbon transition cost calculation model with the objective functions of minimizing power generation combination cost and ancillary service cost, thus quantifying the additional costs generated by developing new energy. Compared with the traditional SCUC model, this application considers the operating characteristics of new energy units, regional consumption requirements, and the safe and stable operation conditions of new energy systems, making it more suitable for new power systems with a high proportion of new energy access.

[0139] (2) Further considering the continuity and stability of production planning, a long-term low-carbon transition cost calculation model was established. Based on the constructed optimized model, different new energy penetration rate scenarios were set to calculate the low-carbon transition cost under different new energy penetration rates, and further calculate the low-carbon transition cost increment. Compared with the calculation model based on the intraday spot time scale, the long-term simulation can cover a wider time range, thus more comprehensively considering the impact of market changes, strategy adjustments and other factors on system costs, and more accurately measuring the low-carbon transition cost of the new power system.

[0140] Based on the same inventive concept, this application also provides a power system low-carbon transformation cost calculation device for implementing the above-mentioned power system low-carbon transformation cost calculation method. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more power system low-carbon transformation cost calculation embodiments provided below can be found in the limitations of power system low-carbon transformation cost calculation above, and will not be repeated here.

[0141] In one exemplary embodiment, such as Figure 5 As shown, a cost calculation device for low-carbon transformation of power systems is provided, comprising:

[0142] The data acquisition module 301 is used to acquire the current operating status of the power system units; the power system includes thermal power units and new energy units.

[0143] The calculation model construction module 302 is used to construct a low-carbon transition cost calculation model. The low-carbon transition cost calculation model includes an objective function and constraints. The objective function is constructed based on the operating costs of thermal power units, the operating costs of new energy units, and the auxiliary service costs of thermal power units. The constraints include: power balance constraints, thermal power unit constraints, new energy unit constraints, and new energy system safety and stability constraints.

[0144] The solution module 303 is used to input the current unit operating status into the low-carbon transformation cost calculation model for solution, and obtain the optimal solution under different new energy penetration rates at the current time; the optimal solution includes: the switching status of each unit in the power system and the output of each unit when the objective function is minimized.

[0145] The low-carbon transition cost determination module 304 is used to input the optimal solutions under different new energy penetration rates at the current time into the objective function, and determine the obtained objective function values ​​under each new energy penetration rate as the low-carbon transition cost under the corresponding new energy penetration rate.

[0146] As an optional implementation, please still refer to Figure 5 The power system low-carbon transformation cost calculation device further includes:

[0147] The cost increment calculation module 305 is used to calculate the difference in low-carbon transition costs under different new energy penetration rates, and obtain the corresponding cost increment.

[0148] The proposed calculation scheme for the cost and cost increment of the low-carbon transformation of the power system quantifies the increased system cost as new energy development reaches different penetration rates, providing a cost reference for the low-carbon transformation of the power system and steadily and orderly promoting the low-carbon transformation of the power system.

[0149] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores the current operating status of the power system's generating units. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When executed by the processor, the computer program implements a method for calculating the cost of low-carbon transformation of the power system.

[0150] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0151] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0152] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0153] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0154] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0155] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, etc., and are not limited to these.

[0156] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for calculating the cost of low-carbon transformation of a power system, characterized in that, The low-carbon transformation cost calculation method of the power system comprises the following steps: An operating state of a unit at a current time is obtained; the power system comprises a thermal power unit and a new energy unit; A low-carbon transformation cost calculation model is constructed; the low-carbon transformation cost calculation model comprises a target function and a constraint condition; the target function is constructed according to a thermal power unit operating cost, a new energy unit operating cost and a thermal power unit auxiliary service cost; the constraint condition comprises a power balance constraint, a thermal power unit constraint, a new energy unit constraint and a new energy system safety and stability constraint; An expression of the target function is as follows: Min F = F1 + F2; wherein, F represents the target function; F1 represents a unit combined power generation cost of the power system; F2 represents a thermal power unit auxiliary service cost; An expression of the thermal power unit auxiliary service cost is as follows: Wherein, f4 represents the cost of providing upper and lower backup of thermal power units; f5 represents the cost of providing deep peak shaving auxiliary service of thermal power units; f6 represents the cost of providing primary and secondary frequency modulation of thermal power units; N T represents the number of time points; N G represents the number of thermal power units; represents the upper backup offer of thermal power unit i at time t; represents the lower backup offer of thermal power unit i at time t; represents the upper backup power provided by thermal power unit i; represents the lower backup power provided by thermal power unit i; represents the deep peak shaving offer of thermal power unit i; represents the deep peak shaving capacity of thermal power unit i; represents the primary frequency modulation mileage price of thermal power unit i at time t; represents the secondary frequency modulation mileage price of thermal power unit i at time t; represents the primary frequency modulation capacity price of thermal power unit i at time t; represents the secondary frequency modulation capacity price of thermal power unit i at time t; represents the primary frequency modulation performance index of thermal power unit i at time t; represents the secondary frequency modulation performance index of thermal power unit i at time t; represents the primary frequency modulation winning capacity of thermal power unit i at time t; represents the secondary frequency modulation winning capacity of thermal power unit i at time t; The new energy system safety and stability constraint comprises an up reserve constraint and a down reserve constraint; A system up reserve demand is determined according to the following formula: wherein, respectively, are the system up and down reserve demand at time t; respectively, are the system up and down reserve demand coefficients at time t; denotes the standard deviation of uncontrollable load power; denotes the standard deviation of wind turbine output power; denotes the standard deviation of photovoltaic unit. A system down reserve demand is determined according to the following formula: wherein, represents the output of the largest-capacity thermal power unit in the system at the maximum load; represents the output of the largest-capacity unit in the system at the minimum load; R up is the upper reserve demand of the system, R dn is the lower reserve demand of the system; The up reserve constraint of the model is as follows: The down reserve constraint is as follows: wherein, Pmax,i represents the maximum output power of the thermal power unit i; P i Pmin,i represents the minimum output power of the thermal power unit i; i,t Pi(t) represents the output power of the thermal power unit i at time t; i,t ui(t) represents whether the thermal power unit i is in an idle state at time t, and is a 0-1 variable, 1 for running and 0 for off-grid running; The operating state of the unit at the current time is input into the low-carbon transformation cost calculation model for solving, to obtain an optimal solution under different new energy penetration rates at the current time; the optimal solution comprises a switch state of each unit in the power system and an output of each unit corresponding to a minimum target function value; The optimal solution under different new energy penetration rates at the current time is input into the target function respectively, and a target function value under each new energy penetration rate is determined as a low-carbon transformation cost under the corresponding new energy penetration rate.

2. The method of claim 1, wherein, After the low-carbon transformation costs under different new energy penetration rates are obtained, the low-carbon transformation cost calculation method of the power system further comprises the following steps: A difference value of the low-carbon transformation costs under different new energy penetration rates is calculated, to obtain a corresponding cost increment.

3. The method of claim 1, wherein, If the current time is an initial time of the day, an operating state of a unit at an end time of the previous day is taken as the operating state of the unit at the current time.

4. The method of claim 1, wherein, An expression of the unit combined power generation cost of the power system is as follows: wherein fi represents the operation cost of the thermal power unit; f2 represents the operation cost of the wind power unit; f3 represents the operation cost of the photovoltaic unit; N G represents the number of thermal power units; M represents the number of time periods; N T represents the number of time points; represents the electricity energy offer of the thermal power unit i at the time point t in the m time period; P i,m,t represents the output of the thermal power unit i at the time point t in the m time period; represents the start-up cost of the thermal power unit i; represents the shut-down cost of the thermal power unit i; represents the no-load operation cost of the thermal power unit i; v i,t represents the start-up action of the thermal power unit i at the time point t; w i,t represents the shut-down action of the thermal power unit i at the time point t; u i,t represents whether the thermal power unit i is in the no-load operation state at the time point t; N W represents the number of wind power units; N PV represents the number of photovoltaic units; represents the offer of the wind power unit j; represents the offer of the photovoltaic unit k; P j,t represents the output power of the wind power unit j at the time point t; P k,t represents the output power of the photovoltaic unit k at the time point t.

5. The method of claim 1, wherein, The thermal power unit constraint comprises a thermal power unit ramping constraint and a thermal power unit start-stop time constraint; the new energy unit constraint comprises a wind power output constraint, a photovoltaic output constraint and a new energy consumption rate constraint; and the new energy system safety and stability constraint comprises a frequency stability constraint, an up reserve constraint, a power flow safety constraint, a node constraint and a system minimum inertia constraint.

6. A device for measuring the cost of low-carbon transformation of a power system, characterized in that, The low-carbon transformation cost calculation device of the power system comprises the following components: A data acquisition module is configured to obtain an operating state of a unit at a current time; the power system comprises a thermal power unit and a new energy unit; A calculation model construction module is configured to construct a low-carbon transformation cost calculation model; the low-carbon transformation cost calculation model comprises a target function and a constraint condition; the target function is constructed according to a thermal power unit operating cost, a new energy unit operating cost and a thermal power unit auxiliary service cost; and the constraint condition comprises a power balance constraint, a thermal power unit constraint, a new energy unit constraint and a new energy system safety and stability constraint; An expression of the target function is as follows: Min F = F1 + F2; Wherein, F represents a target function; F1 represents a unit commitment generation cost of the power system; and F2 represents an auxiliary service cost provided by the thermal power unit; An expression of the auxiliary service cost provided by the thermal power unit is: wherein f4 represents the cost of providing upper and lower backup of the thermal power unit; f5 represents the cost of providing deep peak shaving auxiliary service of the thermal power unit; f6 represents the cost of providing primary and secondary frequency modulation of the thermal power unit; N T represents the number of time points; N G represents the number of thermal power units; represents the upper backup offer of the thermal power unit i at the time point t; represents the lower backup offer of the thermal power unit i at the time point t; represents the upper backup power provided by the thermal power unit i; represents the lower backup power provided by the thermal power unit i; represents the deep peak shaving offer of the thermal power unit i; represents the deep peak shaving capacity of the thermal power unit i; represents the primary frequency modulation mileage price of the thermal power unit i at the time point t; represents the secondary frequency modulation mileage price of the thermal power unit i at the time point t; represents the primary frequency modulation capacity price of the thermal power unit i at the time point t; represents the secondary frequency modulation capacity price of the thermal power unit i at the time point t; represents the primary frequency modulation performance index of the thermal power unit i at the time point t; represents the secondary frequency modulation performance index of the thermal power unit i at the time point t; represents the primary frequency modulation winning capacity of the thermal power unit i at the time point t; represents the secondary frequency modulation winning capacity of the thermal power unit i at the time point t. The new energy system safety and stability constraint includes up and down reserve constraints; The system up and down reserve demand is determined according to the following formula: wherein, respectively, are the system up and down reserve demand at time t; respectively, are the system up and down reserve demand coefficients at time t; denotes the standard deviation of uncontrollable load power; denotes the standard deviation of wind turbine output power; denotes the standard deviation of photovoltaic unit. The system up and down reserve demand is determined according to the following formula: wherein, represents the output of the largest-capacity thermal power unit in the system at the maximum load; represents the output of the largest-capacity unit in the system at the minimum load; up R is the upper reserve demand of the system, dn R is the lower reserve demand of the system; The up reserve constraint of the model is: The down reserve constraint is: wherein, Pmax,i represents the maximum output power of the thermal power unit i; P i Pmin,i represents the minimum output power of the thermal power unit i; i,t Pi(t) represents the output power of the thermal power unit i at time t; i,t ui(t) represents whether the thermal power unit i is in an idle operation state at time t, and is a 0-1 variable, 1 for operation and 0 for off-grid operation; A solving module is configured to input the unit operation state at the current time into the low-carbon transformation cost measurement model for solving to obtain optimal solutions under different new energy penetrations at the current time; the optimal solutions include switch states of each unit in the power system and unit outputs corresponding to the minimum target function value; A low-carbon transformation cost determination module is configured to input the optimal solutions under different new energy penetrations at the current time into the target function respectively, and determine the target function values under each new energy penetration as the low-carbon transformation cost under the corresponding new energy penetration.

7. A computer device comprising: A memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the power system low-carbon transformation cost measurement method of any one of claims 1-5.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the power system low-carbon transformation cost measurement method of any one of claims 1-5.

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