Optimization Method for Balanced Regulation of Supply and Demand of Flexible Resources Considering Source-Network-Load-Storage

Abstract

The present invention provides a method for optimizing the supply-demand balance regulation considering the flexibility resources of the power source, grid, load and storage, belonging to the technical field of optimizing the regulation of power source, grid, load and storage resources; it solves the problem that the existing research does not reasonably quantify the losses caused by insufficient flexibility in the power system, resulting in unsatisfactory optimization effects; the present invention considers the carbon emissions of the whole life cycle of the flexibility resources of the entire power source, grid, load and storage chain, and designs a carbon trading mechanism to promote the low-carbon operation of the flexibility resources; measures the risk losses of abandoned wind and light caused by insufficient flexibility through the CVaR method; constructs a multi-objective flexibility resource balance optimization regulation model to ensure the safe and low-carbon operation of the power system.

Description

Technical Field

[0001] The present invention provides a method for optimizing the regulation of supply-demand balance considering flexible resources of the power grid, the power load, and energy storage, belonging to the technical field of optimizing the regulation of power grid, power load, and energy storage resources. Background Art

[0002] In order to make full use of new energy power generation and reduce the phenomenon of wind and light abandonment, the concept of flexible resources has been proposed in the process of improving the regulation ability of the power system. In the future, the demand for flexible resources in the power system will increase significantly. However, ensuring the real-time balance of the supply and demand of flexible resources in the power system is a difficult problem, which brings challenges to the safe and stable operation of the power grid and also puts forward higher requirements for the flexibility of the power system. Therefore, the coordinated development of flexible resources is an effective way to solve the contradiction between flexible supply and demand. To improve the flexibility of the power system, flexible resources including energy storage systems, pumped-storage systems, and demand response resources need to be connected to the power system. By deeply exploring the potential of various types of potential flexible resources in links such as the power grid, the power load, and energy storage, various types of flexible resources are economically and efficiently configured to jointly meet the development needs of renewable energy.

[0003] Regarding the operation optimization of flexible resources, there have been many studies. Some scholars have proposed setting multiple operation scenarios for different priority targets to stimulate the operation flexibility of distributed energy systems. Some scholars have considered flexibility characteristics such as spatio-temporal coupling and proposed an operation optimization method based on the total regional dispatch budget and carbon emission constraints. Some scholars have proposed a method based on a mixed-integer non-linear optimization model for uncertainties such as load forecasting, weather changes, and equipment failures to achieve the balance between energy planning supply and actual output. Some scholars have proposed a method based on comprehensive flexible regions to characterize and measure comprehensive flexibility, and at the same time consider the time coupling constraints of distributed multi-energy systems, and incorporate the decoupled comprehensive flexible regions into the multi-period economic dispatch of centralized energy systems.

[0004] Currently, the research on the flexibility of the power system mostly focuses on aspects such as supply-demand balance, planning configuration, and dispatch operation, while the research on aspects such as the economic cost and risk cost of flexibility is less. Some scholars have considered the flexibility price in the objective function to reasonably compensate the equipment providing flexibility in the system. Some scholars have proposed that the transmission grid operator obtains benefits by selling flexibility to the distribution grid operator and compensates the flexibility cost of the transmission grid operator. Some scholars have proposed a tradable flexible resource certificate, which is purchased by renewable energy generators or they will not be able to participate in the energy market, which alleviates the problems existing in new power systems such as insufficient flexibility to a certain extent. Some scholars have designed a flexibility score to measure the flexibility degree of a single energy source. The above research on the economic cost and price of flexibility mostly reflects the level of compensating the flexibility value, and there is no further in-depth study on the risk losses caused by insufficient system flexibility.

[0005] In summary, new energy installations will penetrate the power grid generation system at a high proportion. However, the output of new energy is highly volatile and uncertain, and its grid connection operation poses great challenges to the power system. Multiple studies have confirmed that flexible resources play an important role in the high penetration of new energy into the grid, and can effectively reduce the system operation cost and carbon emissions. In existing research, it has been found that insufficient flexibility has a great impact on the safe and stable operation of the power system, but the losses caused by insufficient flexibility in the system have not been reasonably quantified. Summary of the Invention

[0006] To solve the above technical problems, the present invention proposes a supply-demand balance regulation and optimization method considering flexible resources of power sources, grids, loads, and energy storage.

[0007] The technical solution adopted by the present invention is as follows: A supply-demand balance regulation and optimization method considering flexible resources of power sources, grids, loads, and energy storage, comprising the following steps:

[0008] 1) Construct a carbon emission measurement model based on the life cycle energy chain to measure the greenhouse gas emissions directly generated by the power system activities themselves or the input materials.

[0009] 2) Based on the difference between the total carbon emissions of the life cycle energy chain and the carbon quota, construct the carbon trading principle and mathematical model to calculate the CO2 amount of each flexible resource actually participating in carbon trading.

[0010] 3) Set the loss indexes of insufficient upward and downward adjustment of flexible resources, and use the CVaR method to quantitatively analyze the wind and light abandonment losses when the flexible resources are insufficiently adjusted upward and downward.

[0011] 4) Construct a flexibility shortage risk model, and calculate the total loss CVaR values of power system load shedding and wind and light abandonment through the Monte Carlo simulation method.

[0012] 5) Construct a flexible resource cost function to enable the safe and low-carbon operation of the power system.

[0013] In the carbon emission measurement model based on the life cycle energy chain constructed in step 1), the CO2 emissions of the full life cycle of the kth flexible resource are calculated The formula is as follows:

[0014] ;

[0015] ;

[0016] In the formula: is t the full life cycle carbon emissions of the kth flexible resource at time k ; and are respectively tThe upward and downward demands for the k th type of flexibility resource in the power system at a certain moment; For the k th type of flexibility resource, the carbon emission coefficient in the whole life cycle; And respectively represent t at a certain moment, whether the k th type of flexibility resource participates in the upward and downward flexibility regulation of the system, which is a 0-1 variable.

[0017] k =1 represents a thermal power unit with flexibility transformation; k =2 represents a gas turbine; k =3 represents a hydropower unit; k =4 represents an electrochemical energy storage; k =5 represents a pumped-storage power station; k =6 represents a load demand response; k =7 represents grid mutual assistance;

[0018] When k =1, 2, 3, represents the power to increase the output of the flexibility resource, represents the power to reduce the output of the flexibility resource; when k =4, represents the power generation power of the electrochemical energy storage, represents the charging power of the electrochemical energy storage; when k =5, represents the power generation power of the pumped-storage power station, represents the pumping power of the pumped-storage power station; when k =6, represents the reduced electricity load of the user for demand response, represents the increased electricity load of the user for demand response; k =7, represents the reduced grid mutual assistance power, represents the increased grid mutual assistance power.

[0019] The carbon trading principle and mathematical model constructed in step 2) are for the part where the actual carbon emissions are greater than the quota to participate in the participatory carbon trading after deducting the quota from the flexibility resource k . The expression of the mathematical model is as follows:

[0020] ;

[0021] ;

[0022] In the formula: is the kThe trading volume of a certain type of flexibility resource participating in the carbon market; For the k carbon quota of a certain type of flexibility resource; For the k cost or revenue of a certain type of flexibility resource participating in the carbon market. When is positive, it indicates the revenue obtained by a certain type of flexibility resource participating in the carbon market. When k is negative, it indicates the cost incurred by a certain type of flexibility resource participating in the carbon market; For the k carbon trading unit price; For the T life cycle of the flexibility resource; Δ T For the length of a certain period within the life cycle of the flexibility resource.

[0023] The expressions for the under-regulation loss indicators of the flexibility resource set in step 3) are as follows:

[0024] ;

[0025] In the formula: and are respectively the under-regulation losses of the flexibility resource for upward and downward regulation at t moment; For the t unit cost of insufficient upward regulation of the flexibility resource at moment, that is, the cost of load shedding loss; t For the unit cost of insufficient downward regulation of the flexibility resource at t moment, that is, the cost of wind and solar curtailment loss; For the t net load upward regulation demand at moment; For the t net load downward regulation demand at

[0026] Among them:

[0027] ;

[0028] ;

[0029] In the formula: L t,net For the t net load of the power system at and are respectively the upward and downward demands for the t th type of flexibility resource within the power system at k moment; and respectively t the k whether the nth flexibility resource participates in the upward and downward flexibility regulation of the system, which is a 0-1 variable.

[0030] The flexibility shortage risk model constructed in step 4) uses the CVaR model to quantitatively analyze the risk costs when the flexibility resources are insufficient in upward and downward regulation. Based on the confidence level of the new energy power generation output deviation, it reflects the uncertainty of new energy, and its deviation loss does not exceed the critical value α The specific calculation formula of the probability is as follows:

[0031] ;

[0032] ;

[0033] In the formula: α is that the deviation loss of the new energy power generation output does not exceed the critical value; Prob ( ) is the probability function; 、 is the probability density function;

[0034] At the confidence level β calculate the CvaR of the power system load shedding and curtailment of wind losses, and the specific formula is as follows:

[0035] ;

[0036] ;

[0037] In the formula: is the confidence level β under t the conditional risk value of the system load shedding during the period; is the confidence level β under t the conditional risk value of the system curtailment of wind during the period; ;

[0038] Through the Monte Carlo simulation method, select random 、 variables of M 、 N discrete points as sample points, and calculate the total loss CVaR values of the power system load shedding and curtailment of wind and light, and the specific formula is as follows:

[0039] ;

[0040] In the formula: is t the estimated value of the probability density function of the loss due to insufficient flexibility in upward and downward regulation during the period; ist Estimated probability density function value of the loss due to insufficient flexibility in the upward adjustment during period t; is the estimated probability density function value of the loss due to insufficient flexibility in the downward adjustment during period t.

[0041] The expression of the flexibility resource cost function constructed in step 5) is as follows:

[0042] ;

[0043] The constraint conditions are as follows:

[0044] ;

[0045] In the formula: C sys is the total cost of the flexibility resources in the power system; is the carbon emission cost of the flexibility resources; is t the operating cost of the k th type of flexible retrofitted thermal power and gas turbine flexibility resources during period t; is t the operating cost of the k th type of flexibility resources such as hydropower, electrochemical energy storage, pumped-storage energy storage, load demand response, and grid interconnection during period t; is the conditional value at risk of system load shedding during period t under the confidence level β ; t is the conditional value at risk of system wind curtailment during period t under the confidence level ; β ; t is the conditional value at risk of system wind curtailment during period t; is t the power generation power of the flexible retrofitted thermal power unit during period t i ; , are respectively the charging and discharging powers of the electrochemical energy storage during period t ; is t the power generation power of the pumped-storage energy storage during period t; is t the pumping power of the pumped-storage energy storage during period t; is t the load power that can be shifted to other periods during period t; is t the load power that can be curtailed during period t; is t the load power that can be shifted to this period during period t; is t the load shedding power during period t; is the wind curtailment power of the new energy during period t ; Ni The number of thermal power units retrofitted for flexibility.

[0046] ;

[0047] ;

[0048] In the formula: a k is the quadratic term unit cost coefficient of the k th type of thermal power unit retrofitted for flexibility and gas turbine; b k is the linear term unit cost coefficient of the k th type of flexibility resource; c k is the constant term fixed cost coefficient of the k th type of flexibility resource.

[0049] The power generation power constraints of the thermal power units retrofitted for flexibility include: the power of the generator sets retrofitted for flexibility, the shortest start-up and shutdown times, the unit operation status at a certain moment, and the unit start-up and shutdown status constraints at a certain moment;

[0050] The load demand response constraints include: the constraints of shiftable load and the constraints of curtailable load. Among them, the constraints of shiftable load include: the power of the load that can be shifted to other time periods in a certain time period, the power of the load that can be shifted to this time period in a certain time period, and the flag constraints of the shifted load;

[0051] The constraints of curtailable load include the power constraints of curtailable load in a certain time period;

[0052] The electrochemical energy storage constraints include: the allowable electricity of electrochemical energy storage, the charging and discharging power of electrochemical energy storage in a certain time period, and the charging and discharging status constraints;

[0053] The pumped-storage energy storage constraints include: the power generation and pumping power of pumped-storage energy storage in a certain time period, and the power generation, pumping status constraints and the upper reservoir energy storage constraints of pumping.

[0054] The beneficial effects of the present invention compared with the prior art are as follows: The present invention considers the whole-life cycle carbon emissions of flexibility resources in the entire source-network-load-storage chain, designs a carbon trading mechanism to promote the low-carbon operation of flexibility resources; measures the risk loss of abandoned wind and light caused by insufficient flexibility through the CVaR method; constructs a multi-objective flexibility resource balance optimization and control model to ensure the safe and low-carbon operation of the power system.

[0055] Moreover, existing studies generally rely on multiple inequality constraints when considering economy and low carbon, while the multi-objective flexibility resource balance optimization and control model proposed in the present invention incorporates a carbon trading mechanism, which can simultaneously stimulate the contributions of flexibility resources in economy and low carbon.

[0056] Moreover, from the perspective of the safe and stable operation of the power system, the present invention quantifies the risk cost brought by insufficient flexibility, effectively reducing the losses of load shedding and curtailment of wind and light. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention will be further described below with reference to the accompanying drawings:

[0058] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0059] As Figure 1 shown, the present invention provides a supply-demand balance regulation and optimization method considering flexibility resources of power sources, grids, loads, and energy storage, including the following steps:

[0060] 1) Construct a carbon emission measurement model based on the life-cycle energy chain to measure the greenhouse gas emissions directly generated by the power system activities themselves or the input materials, considering the conversion accompanying effects related to the operation of the power system or materials. The measurement scope of the life-cycle carbon emissions of power sources, grids, loads, and energy storage is from the source to the grid to the load and then to the energy storage, excluding the transmission and distribution links of secondary energy.

[0061] 2) Based on the difference between the total carbon emissions of the life-cycle energy chain and the carbon quota, construct a carbon trading principle and mathematical model to calculate the CO2 amount of each flexibility resource actually participating in carbon trading.

[0062] 3) Set the loss indexes of insufficient upward and downward adjustment of flexibility resources, and use the CVaR method to quantitatively analyze the curtailment losses of wind and light when the flexibility resources are insufficiently adjusted upward and downward.

[0063] 4) Construct a flexibility deficiency risk model, and calculate the total loss CVaR values of load shedding and curtailment of wind and light in the power system through the Monte Carlo simulation method.

[0064] 5) Design a cost function of flexibility resources, and based on the principle that the total supply of flexibility resources in the power system is equal to the total demand (net load), design the constraint conditions of a multi-objective flexibility resource balance optimization regulation model. Thus, a multi-objective flexibility resource balance optimization regulation model is obtained, enabling the safe and low-carbon operation of the power system.

[0065] In step 1), the constructed carbon emission measurement model uses the life-cycle carbon emission analysis method of power sources, grids, loads, and energy storage to measure the greenhouse gas emissions directly generated by the power system activities themselves or the input materials, considering the conversion accompanying effects related to the operation of the power system or materials. The measurement scope of the life-cycle carbon emissions of power sources, grids, loads, and energy storage is from the source to the grid to the load and then to the energy storage, excluding the transmission and distribution links of secondary energy.

[0066] To reflect that the sum of the carbon emissions of the corresponding operating equipment in each stage is the total carbon emissions of the source-grid-load-storage chain of flexibility resources, the present invention calculates the CO2 emissions of the k-th type of flexibility resource over the entire life cycle based on the life cycle of flexibility resources :

[0067] (1);

[0068] (2);

[0069] Where: is t the carbon emissions of the entire life cycle of the k th type of flexibility resource at time and are respectively t the upward and downward demands for the k th type of flexibility resource within the power system at time is the carbon emission coefficient of the entire life cycle of the k th type of flexibility resource; and are respectively t whether the k th type of flexibility resource participates in the upward and downward flexibility regulation of the system, which is a 0-1 variable.

[0070] Among them, k = 1 represents a thermal power unit with flexibility retrofit; k = 2 represents a gas turbine; k = 3 represents a hydropower unit; k = 4 represents an electrochemical energy storage; k = 5 represents a pumped-storage power station; k = 6 represents a load demand response; k = 7 represents grid mutual assistance.

[0071] When k = 1, 2, 3, represents the power to increase the output of the flexibility resource, represents the power to reduce the output of the flexibility resource; when k = 4, represents the power generation of the electrochemical energy storage, represents the charging power of the electrochemical energy storage; when k = 5, represents the power generation of the pumped-storage power station, represents the pumping power of the pumped-storage power station; when k = 6, represents the reduced electricity load of the user for demand response, represents the increased electricity load of the user for demand response; k = 7, represents the reduced grid mutual assistance power, represents the increased grid mutual assistance power.

[0072] Let: (3);

[0073] In the formula: P k,t is the k th type of flexibility resource t at time

[0074] The carbon trading principle and mathematical model constructed in step 2) are for the part where the actual carbon emissions exceed the quota to participate in the participatory carbon trading after deducting the quota from the flexibility resource k . The expression of this mathematical model is as follows:

[0075] (4);

[0076] (5);

[0077] In the formula: is the trading volume of the k th type of flexibility resource participating in the carbon market; is the carbon quota of the k th type of flexibility resource; is the cost or benefit of the k th type of flexibility resource participating in the carbon market. When is positive, it means the benefit obtained by the k th type of flexibility resource participating in the carbon market. When is negative, it means the cost paid by the k th type of flexibility resource participating in the carbon market; is the unit price of carbon trading; T is the life cycle of the flexibility resource; Δ T is the length of a certain period within the life cycle of the flexibility resource.

[0078] The calculation process of the flexibility resource upward and downward adjustment deficiency loss index set in step 3) is as follows:

[0079] Let:

[0080] (6);

[0081] In the formula: L t,net is the t net load of the power system at time L t is the t user load at time is the t wind power at time is the t photovoltaic power at time P k,t is the k th type of flexibility resource t at time

[0082] Let:

[0083] (7);

[0084] (8);

[0085] Then:

[0086] (9);

[0087] Wherein: is t the upward regulation demand of the net load at time is t the downward regulation demand of the net load at time and are respectively t the total upward and downward supply capabilities of the power system flexibility resources at time and are respectively t the losses of insufficient upward and downward regulation of the flexibility resources at time is t the unit cost of insufficient upward regulation of the flexibility resources at time, that is, the cost of load shedding loss, and can be calculated and analyzed with reference to the interruptible electricity price; is t the unit cost of insufficient downward regulation of the flexibility resources at time, that is, the cost of wind and light abandonment loss, and can be calculated and analyzed according to the prices of wind power and photovoltaic power; K is the type of flexibility resources.

[0088] When there is insufficient upward flexibility, the power system will face the risk of load shedding; when there is insufficient downward flexibility, the power system will have the risk of wind and light abandonment. Therefore, a flexibility shortage risk model is constructed, the penalty cost of insufficient flexibility resources is introduced, and through the operation simulation of a typical day, iterative feedback is carried out according to whether the flexibility supply-demand balance constraint is satisfied to realize the optimal allocation of flexibility resources.

[0089] The present invention uses the CVaR model to quantitatively analyze the risk costs when the flexibility resources are insufficient in upward and downward regulation, and reflects the uncertainty of new energy based on the confidence level of the new energy power generation deviation. The specific calculation formula for the probability that the loss of the new energy power generation deviation does not exceed the critical value α is as follows:

[0090] (10);

[0091] (11);

[0092] Wherein: αThe deviation loss of new - energy power generation output does not exceed the critical value; Prob ( ) is the probability that the up - regulation and insufficient down - regulation losses of flexible resources do not exceed the critical value; its probability density function 、 is difficult to calculate. Through the Monte Carlo simulation method, discrete points of the random variable M 、 N are selected as sample points.

[0093] In the present invention, the CvaR of the load shedding and wind curtailment losses of the power system is calculated at the confidence level β as follows: the specific formula is as follows:

[0094] (12);

[0095] (13);

[0096] In the formula: is the conditional value - at - risk of the system load shedding (insufficient up - regulation flexibility) in the β period at the confidence level t ; is the conditional value - at - risk of the system wind curtailment (insufficient down - regulation flexibility) in the β period at the confidence level t ; .

[0097] In the present invention, through the Monte Carlo simulation method, discrete points of the random 、 variables M 、 N are selected as sample points to calculate the total loss CVaR value of the system load shedding and wind and PV curtailment. The specific formula is as follows:

[0098] (14);

[0099] In the formula: is the estimated value of the probability density function of the up - and - down regulation flexibility deficiency loss in the t period; is the estimated value of the probability density function of the insufficient up - regulation flexibility loss in the t period; is the estimated value of the probability density function of the insufficient down - regulation flexibility loss in the t period.

[0100] The expression of the flexible resource cost function designed in step 5) is as follows:

[0101] (15);

[0102] (16);

[0103] Wherein: is t the operating cost of the k th (representing flexible retrofitted thermal power and gas turbines here) type of flexibility resource in the time period; is t the operating cost of the k th (representing hydropower, electrochemical energy storage, pumped-storage hydropower, load demand response and grid interconnection here) type of flexibility resource in the time period; a k is the quadratic term unit cost coefficient of the kth type of flexible retrofitted thermal power unit and gas turbine; b k is the linear term unit cost coefficient of the kth type of flexibility resource; c k is the constant term fixed cost coefficient of the kth type of flexibility resource.

[0104] The expression of the multi-objective flexibility resource balance optimization and regulation model constructed in step 5) is as follows:

[0105] (17);

[0106] The constraint condition of the above objective function is that the total supply of flexibility resources in the power system is equal to the total demand (net load), as shown in the following formula:

[0107] (18);

[0108] Wherein: C sys is the total cost of flexibility resources in the power system; is the carbon emission cost of flexibility resources; is t the power generation power of the flexible retrofitted thermal power unit in the i time period; , are respectively the charging and discharging powers of the electrochemical energy storage in the t time period; is t the pumped-storage hydropower generation power in the time period; t is the pumping power of the pumped-storage hydropower in the t time period; is t the load power that can be shifted to other time periods in the time period; t is the load power that can be shifted to this time period in the t time period; For new energy during t the abandoned power of the power generation unit during a period; N i is the number of thermal power units with flexibility transformation.

[0109] The specific expressions of each constraint are as follows.

[0110] a. The power generation power constraint of the thermal power unit with flexibility transformation is as follows:

[0111] (19);

[0112] (20);

[0113] (21);

[0114] (22);

[0115] In the formula: is the minimum power generation power of the thermal power unit with flexibility transformation i ; is the maximum power generation power of the thermal power unit with flexibility transformation i ; is the rising ramp rate of the thermal power unit with flexibility transformation i ; is the falling ramp rate of the thermal power unit; is t the start-up time of the traditional thermal power unit at the -1 moment tro ; , are respectively the shortest start-up and shutdown times of the traditional thermal power unit tro ; is t the operating state of the traditional thermal power unit at the moment tro ; is t the shutdown time of the traditional thermal power unit at the -1 moment tro ; , are respectively t the start-up and shutdown states of the traditional thermal power unit at the moment tro , which are 0-1 variables.

[0116] b. The load demand response constraint is as follows:

[0117] The flexibility supply on the load side is mainly used to provide a certain proportion of demand response. It can be divided into shiftable load and curtailable load. Among them, the shiftable load means that the total load on the user side remains unchanged, only the power consumption time is changed, while the curtailable load directly interrupts the load without shifting.

[0118] c. The constraints for shiftable loads are as follows:

[0119] (23);

[0120] (24);

[0121] (25);

[0122] Where: and are respectively t the maximum and minimum load powers that can be shifted to other time periods during the and are respectively t the maximum and minimum load powers that can be shifted in from other time periods during the time period and are respectively t the flags indicating whether to shift the load during the

[0123] d. The expression for the load that can be curtailed is as follows:

[0124] (26);

[0125] Where: is t the maximum load that can be curtailed during the is t the flag indicating whether to curtail the load during the

[0126] e. The constraints for the electrochemical energy storage are as follows:

[0127] (27);

[0128] (28);

[0129] (29);

[0130] (30);

[0131] Where: E t is t the stored electricity of the electrochemical energy storage during the E max and E min are t the maximum and minimum stored electricity of the electrochemical energy storage during the and are respectively the charging and discharging efficiencies of the electrochemical energy storage; , are respectively t the maximum charging and discharging powers of the electrochemical energy storage during the and are respectively t the minimum charging and discharging powers of the electrochemical energy storage during the and are respectively t the charging and discharging powers of the electrochemical energy storage during the p k,t and l k,t are respectively t the charging and discharging states of the electrochemical energy storage during the , which are 0-1 variables; Δ t is the scheduling time interval of the electrochemical energy storage.

[0132] The constraints of the pumped-storage energy storage are as follows:

[0133] (31);

[0134] (32);

[0135] (33);

[0136] (34);

[0137] In the formula: and are respectively T the power generation and pumping powers of the pumped-storage energy storage during the ’ and are respectively t the states of power generation and pumping of the pumped-storage energy storage at the moment, which are 0-1 variables; and are respectively the maximum and minimum power generation powers of the pumped-storage energy storage; and are respectively the maximum and minimum pumping powers of the pumped-storage energy storage; is t the energy storage in the upper reservoir of the pumped-storage energy storage during the ; and are the pumping and power generation operation efficiencies of the pumped-storage energy storage units; and are respectively the maximum and minimum energy storages in the upper reservoir of the pumped-storage energy storage.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the regulation of supply-demand balance considering flexible resources of the source, grid, load, and storage, characterized in that: It includes the following steps: 1) Construct a carbon emission measurement model based on the life-cycle energy chain to measure the greenhouse gas emissions directly generated by the activities of the power system itself or the input materials; Calculate the CO2 emissions of the entire life cycle of the k-th type of flexibility resource in the carbon emission measurement model based on the life cycle energy chain constructed in step 1). The formula is as follows: ； ； Where: for t Moment k Carbon emissions of the flexible resource over its entire life cycle; and They are t At any time, the power system k Flexibility to meet both upward and downward resource demands; For the k The carbon emission coefficient of the flexible resource over its entire life cycle; and They are t Moment k Whether the flexibility resource participates in the upward and downward flexibility adjustment of the system, which is a 0-1 variable; k = 1 represents a flexible retrofitted thermal power unit; k = 2 represents a gas turbine; k = 3 represents a hydropower unit; k = 4 represents electrochemical energy storage; k = 5 represents pumped - storage; k = 6 represents load demand response; k = 7 represents grid mutual support; When k = 1, 2, 3, represents the power to increase the output of flexibility resources, represents the power to reduce the output of flexibility resources; when k = 4, represents the power generation power of electrochemical energy storage, represents the charging power of electrochemical energy storage; When k = 5, represents the pumped - storage power generation, represents the pumped - storage pumping power; when k = 6, represents the reduced electricity load due to the user's demand response, represents the increased electricity load due to the user's demand response; k = 7, represents the reduced grid - interconnected power, represents the increased grid - interconnected power; 2) Based on the difference between the total carbon emissions of the life-cycle energy chain and the carbon quota, construct the carbon trading principle and mathematical model to calculate the CO2 amount of each flexibility resource actually participating in carbon trading; The carbon trading principle and mathematical model constructed in step 2) are based on flexible resources k After deducting the quota, the part where the actual carbon emissions are greater than the quota participates in the participatory carbon trading. The expression of the mathematical model is as follows: ； ； In the formula: is the trading volume of the k th type of flexibility resource participating in the carbon market; is the carbon quota of the k th type of flexibility resource; is the cost or benefit of the k th type of flexibility resource participating in the carbon market. When is positive, it indicates the benefit obtained by the k th type of flexibility resource participating in the carbon market. When is negative, it indicates the cost paid by the k th type of flexibility resource participating in the carbon market; is the unit price of carbon trading; T is the life cycle of the flexibility resource; Δ T is the length of a certain period within the life cycle of the flexibility resource; 3) Set the loss indicators for insufficient upward and downward regulation of flexibility resources, and use the CVaR method to quantitatively analyze the curtailment losses of wind and light when the flexibility resources are insufficient for upward and downward regulation; The expressions of the loss indicators for insufficient upward and downward regulation of flexibility resources set in step 3) are as follows: ； Wherein: and are respectively t the losses of insufficient upward and downward regulation of flexibility resources at time is t the unit cost of insufficient upward regulation of flexibility resources at time , that is, the cost of load shedding loss; is t the unit cost of insufficient downward regulation of flexibility resources at time , that is, the cost of wind and light abandonment loss; is t the upward regulation demand of the net load at time ; is t the downward regulation demand of the net load at time ; and are respectively t the total upward and downward supply capabilities of the power system flexibility resources at time ; Where: ； ； Wherein: L t,net is t the net load of the power system at a moment; and are respectively t the upward and downward demands for the k th type of flexibility resource in the power system at a moment; and are respectively t whether the k th type of flexibility resource participates in the upward and downward flexibility regulation of the system at a moment, which is a 0-1 variable; 4) Construct a flexibility deficiency risk model, and calculate the total loss CVaR values of load shedding and curtailment of wind and light in the power system through the Monte Carlo simulation method; The risk model of insufficient flexibility constructed in step 4) uses the CVaR model to quantitatively analyze the risk costs when the flexibility resources are insufficiently increased or decreased. Based on the confidence level of the new energy power generation output deviation, it reflects the uncertainty of new energy, and the deviation loss does not exceed the critical value α The specific calculation formula of the probability is as follows: ； ； Wherein: α The deviation loss of new energy power generation output does not exceed the critical value; Prob ( ) is the probability function; , is the probability density function; Calculate the CvaR of power system load shedding and wind curtailment loss at the confidence level β as follows. The specific formula is as follows: ； ； Where: is the conditional value at risk of system load shedding during the β period under the t confidence level; is the conditional value at risk of system wind curtailment during the β period under the t confidence level; ; By using the Monte Carlo simulation method, randomly select , variables of M , N discrete points as sample points, and calculate the total loss CVaR value of load shedding and wind and photovoltaic curtailment in the power system. The specific formula is as follows: ； In the formula: is t the estimated value of the probability density function of the loss due to insufficient flexibility in the up and down regulation during the period; is t the estimated value of the probability density function of the loss due to insufficient flexibility in the up regulation during the period; is the estimated value of the probability density function of the loss due to insufficient flexibility in the down regulation during the t period; 5) Construct a flexibility resource cost function to enable the safe and low-carbon operation of the power system; The expression of the flexibility resource cost function constructed in step 5) is as follows: ； The constraint conditions are as follows: ； where: C sys is the total cost of flexibility resources in the power system; is the carbon emission cost of flexibility resources; is t the k operation cost of the is t the k operation cost of the flexibility resources of hydropower, electrochemical energy storage, pumped-storage hydropower, load demand response, and grid interconnection in the is the conditional value at risk of system load shedding in the β under the t confidence level; is the conditional value at risk of system wind curtailment in the β under the t confidence level; is t the power generation of the flexible retrofitted thermal power unit in the i period; , are respectively the charging and discharging powers of the electrochemical energy storage in the t period; is t the power generation of the pumped-storage hydropower in the is t the pumping power of the pumped-storage hydropower in the is t the load power that can be shifted to other periods in the is t the load shedding power in the is t the load power that can be shifted to this period in the is t the load shedding power in the is the wind curtailment power of new energy in the t period; N i is the number of flexible retrofitted thermal power units.

2. The supply-demand balance regulation and optimization method considering flexibility resources of source, grid, load and energy storage according to claim 1, characterized in that: ； ； Wherein: a k is the quadratic term unit cost coefficient of the k th flexible retrofit thermal power unit and gas turbine; b k is the linear term unit cost coefficient of the k th flexible resource; c k is the constant term fixed cost coefficient of the k th flexible resource.

3. The supply-demand balance regulation optimization method considering flexible resources of power generation, grid, load and energy storage according to claim 1, characterized in that: The power generation power constraints of the flexibly retrofitted thermal power units include: the power of the flexibly retrofitted generating units, the shortest start-up and shutdown times, the unit operation state at a certain moment, and the unit start-up and shutdown state constraints at a certain moment; The load demand response constraints include: the constraints of shiftable loads and the constraints of reducible loads. Among them, the constraints of shiftable loads include: the power of the load that can be shifted to other time periods in a certain time period, the power of the load that can be shifted to this time period in a certain time period, and the flag constraints of the shifted load; The constraints of reducible loads include the power constraints of the load that can be reduced in a certain time period; The electrochemical energy storage constraints include: the allowable electricity of the electrochemical energy storage, the charging and discharging power of the electrochemical energy storage in a certain time period, and the charging and discharging state constraints; The pumped-storage energy storage constraints include: the power generation and pumping power of the pumped-storage energy storage in a certain time period, and the power generation, pumping state constraints and the storage energy constraint of the upper reservoir during pumping.

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