Method and system for joint clearing of electric energy and reserve service considering security check

Abstract

The application provides a method and system for joint clearing of electric energy and reserve service considering safety check, and belongs to the technical field of power system dispatching operation. The method comprises the following steps: establishing a risk cost model of insufficient upper and lower reserves of a system; based on the risk cost model, establishing a joint clearing model of electric energy and reserve market with the minimum operation cost as the target; based on the joint clearing model of electric energy and reserve market, establishing a robust optimization model for new energy output uncertainty; obtaining the optimal reserve capacity and the optimal winning reserve capacity of the system reserve subject by solving the robust optimization model, and adjusting the optimal reserve capacity when the optimal reserve capacity does not meet the N-1 safety check, and re-optimizing the adjusted optimal reserve capacity to obtain the optimal winning reserve capacity of the system reserve subject meeting the N-1 safety check. N -1 safety check, adjusting the optimal reserve capacity when the optimal reserve capacity does not meet the N -1 safety check, and re-optimizing the adjusted optimal reserve capacity to obtain the optimal winning reserve capacity of the system reserve subject meeting the N-1 safety check.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system dispatching operation, and particularly relates to a method and system for joint clearing of electric energy and reserve service considering safety checking. BACKGROUND

[0002] In order to ensure safe and reliable operation of the power system, a certain reserve capacity needs to be reserved to cope with random faults, load and new energy output prediction errors and other uncertain factors. The large amount of random new energy access makes the system reserve face greater pressure. Since the thermal power unit has good response ability and usually occupies a large proportion of installed capacity, it is easy to be selected as the main source of reserve capacity, so whether it is during high load period to let the generator reserve reserve not to respond to the demand for electricity, or during low load period to short-term increase the unit and run at low load rate to provide reserve, it is uneconomical and even unreliable for the system and the power generation side.

[0003] With the continuous advancement of power market reform, the trading mechanism of the current power market in China is more flexible, and the trading products are transitioning from a single electric energy market to a multi-type market with electric energy and auxiliary services in parallel, and the trading subjects are expanding from single power generation side resources to source and load multi-type resources. Reserve market operation can drive the reasonable distribution of reserve resources on the power generation and load sides through market forces, but cannot obtain the optimal total benefit of electric energy and reserve. Flexible load can provide reserve capacity for the system by interrupting or shifting part of the load in time, reducing the pressure of thermal power units reserving reserve.

[0004] When the electric energy market and the reserve market are cleared in the day-ahead, the power generation side can make bids based on its own generation cost, start-up cost and reserve dispatching cost, and the flexible load user can report the adjustable capacity and price in different periods in the day-ahead based on the electricity income and reserve dispatching cost, and the trading agency can clear the market according to the principle of maximizing social welfare under certain system constraint conditions. A joint clearing model of the day-ahead electric energy market and the reserve auxiliary service market on the power generation side is established, and there are few studies on the joint market of electric energy and reserve auxiliary service participated by both the generator unit and the flexible load. In addition, the reserve capacity optimization based on economic cost may ignore the N-1 safety check of the system, which may cause safety hazards to the system. SUMMARY

[0005] Therefore, the present application provides a method and system for joint clearing of electric energy and reserve service considering safety checking, which comprehensively considers factors such as the characteristics of flexible load, risks caused by insufficient upper and lower reserve, and net load uncertainty, and performs reserve capacity correction considering N-1 safety check through the establishment of a joint clearing model of the day-ahead electric energy and reserve auxiliary service market participated by both the power generation and the load, so as to reduce the safety hazards of the system.

[0006] The technical solution adopted by the embodiments of the present invention to solve its technical problem is as follows:

[0007] A method for joint clearing of electrical energy and standby services considering safety verification includes:

[0008] Step S1: Establish a risk cost model for insufficient upper and lower reserves in the system;

[0009] Step S2: Based on the risk cost model, establish a joint clearing model for the electricity and standby markets with the goal of minimizing operating costs;

[0010] Step S3: Based on the joint clearing model of the electric energy and reserve market, establish a robust optimization model to address the uncertainty of new energy output.

[0011] Step S4: Solve the robust optimization model to obtain the optimal reserve capacity and the optimal bid-winning reserve capacity of the system's reserve body. Perform an N-1 safety check on the optimal reserve capacity. If the N-1 safety check is not met, adjust the optimal reserve capacity and re-optimize and clear the updated optimal reserve capacity to obtain the optimal bid-winning reserve capacity of the system's reserve body that meets the N-1 safety check. The system's reserve body includes generating units and flexible loads. Flexible loads include interruptible loads and transferable loads. The optimal system reserve capacity is composed of the bid-winning reserve capacity of each generating unit and flexible load.

[0012] Preferably, the risk cost model expression is:

[0013]

[0014] In the formula, A(R) t (This refers to risk costs.) The cost of backup risk caused by insufficient backup in the system. R represents the down-reserve risk cost caused by insufficient down-reserve in the system. t This represents the total system reserve capacity.

[0015] The above backup risk cost The cost of load loss caused by unit failures and net load forecasting errors is expressed as:

[0016]

[0017] In the formula, C represents the system's upper reserve capacity at time t; L Cost per unit of load loss; Let be the expected value of the system's reserve deficit at time t. The expression is:

[0018]

[0019]

[0020]

[0021]

[0022] In the formula, PR G,i,t Let PR be the probability of unit i failing at time t; i,t Let PR be the probability of unit i failing at time t; y,t Let Ω be the probability of unit y failing at time t; G For all units; Represents the system's reserve deficit; Ω IL Ω SL These are interruptible and transferable load sets, respectively; P i,t Let i be the amount of wastewater discharged from unit i at time t. The reserve capacity of conventional unit i at time t; These represent the standby capacity of interruptible load j and transferable load k at time t, respectively; δ D,t Let be the net load forecast error at time t, which follows a mean of 0 and a standard deviation of σ. D,t The normal distribution of , where:

[0023]

[0024]

[0025]

[0026] In the formula, P D,t The actual net load value at time t. Let t be the predicted net load value at time t; t∈Ω T Ω T For statistical time sets;

[0027] The following backup risk cost The expression is:

[0028]

[0029] In the formula, C represents the system's reserve capacity at time t; G Cost of decommissioning a unit of generating capacity; Let be the expected value of the reserve deficit in the system at time t. The expression is:

[0030]

[0031] PRL,t =q C / (q C +q L )

[0032]

[0033]

[0034]

[0035]

[0036] In the formula, the probability of unplanned system outage PR L,t q is the ratio of the cumulative power outages caused by factors other than unit failures to the total power demand within the historical observation period of the month in which time t is located; c q L These represent the cumulative power outage and power supply during the historical observation period of the month in which time t is located; For backup shortages in the system; P L,t Let ε be the load vector of all nodes at time t; L,t The average percentage of out-of-service load when unplanned outages occur at time t; The reserve capacity of the transferable load k at time t; These represent the load outage power, load demand, and percentage of unplanned load outages at time t within the historical observation period, excluding unit failures, during the xth unplanned load outage. N represents the cumulative number of load outages at time t within the historical observation period. P represents the reserve capacity of conventional unit i at time t. SL,k,t q represents the winning bid power at time t for transferable load k in the electricity market; Δt is the statistical time interval; q SL,k Let k be the total electricity demand of the transferable load during the scheduling period.

[0037] Preferably, the objective function of the joint clearing model for the electricity and reserve markets, which aims to minimize operating costs, is:

[0038]

[0039] In the formula, C(P) i,t Let be the power generation cost quotation function for conventional unit i at time t; and These are the bid-winning status variables for the reserve capacity of conventional unit i at time t and the bid-winning status variables for the reserve capacity at time t, respectively. A value of 1 indicates that the bid has been won and a value of 0 indicates that the bid has not been won. These are the bidding functions for conventional unit i in the upper reserve market and the bidding functions for conventional unit i in the lower reserve market, respectively. Let j be the bidding function for interruptible load j in the upper standby market; These are the bid functions for the transferable load k in the upper and lower standby markets, respectively; S i The startup cost of conventional unit i; Let i be the start / stop state variable of a conventional unit i at time t. A value of 1 indicates power-on, and a value of 0 indicates power-off; u IL,j,t Let u be the state variable of the interruptible load j at time t. IL,j,t A value of 1 indicates that the interruptible function is enabled, and a value of 0 indicates that the interruptible function is not enabled. and These are the bidding status variables of the transferable load k at time t, representing the reserve capacity at the beginning and end of the bidding process. A value of 1 indicates that the bid has been won, and a value of 0 indicates that the bid has not been won.

[0040] The power generation cost C(P) of conventional generating units i,t ), Quotation function for the backup market Quotation function for the next standby market The expressions are as follows:

[0041]

[0042]

[0043]

[0044] In the formula, a i,1 a i,2 a i,3 These are the bidding coefficients for conventional unit i in the electricity market; m i,1 m i,2 m i,3 These are the standby bid coefficients for conventional unit i in the standby market; m′ i,1 m′ i,2 m′ i,3 These are the standby bid coefficients for conventional unit i in the standby market;

[0045] In the standby market, the standby bid function for interruptible loads. and the standby quotation function for transferable loads They are respectively:

[0046]

[0047]

[0048] In the formula, g i,1 gi,2 g i,3 These represent the standby bid coefficients for interruptible load j in the standby market; g k,1 g k,2 g k,3 These are the standby bid coefficients for transferable load k in the standby market;

[0049] The standby bid function for transferable load in the standby market is:

[0050]

[0051] In the formula, g' k,1 g' k,2 g' k,3 These are the standby bid coefficients for transferable load k in the standby market;

[0052] The constraints for the joint clearing of spot market electricity and reserve market include system power balance, minimum start-up and shutdown time constraints for conventional units, reserve capacity constraints for conventional units, flexible load constraints, line safety constraints, unit ramp rate constraints, and upper and lower limits of unit output after considering the reserve market.

[0053] The system power balance constraint is:

[0054]

[0055] In the formula, Ω W A collection of wind turbine units; Ω is the predicted output value of the wind turbine w at time t; PV A collection of photovoltaic units; Ω is the predicted output value of photovoltaic unit n at time t. E For the system node set; P represents the predicted load on node e at time t. DC,t The total power of all inter-provincial connection lines at time t, with outgoing power being positive and incoming power being negative;

[0056] The minimum start-up and shutdown time constraints for conventional generating units are:

[0057]

[0058] In the formula, , respectively, represent the minimum continuous start-up time and minimum continuous downtime of conventional unit i; m is the time point;

[0059] The conventional unit standby capacity constraint is:

[0060]

[0061]

[0062] In the formula, τ is the ramp rate of conventional unit i; τ is the response time of the standby capacity. For conventional unit i, the downhill ramp rate is... and P i These are the upper and lower limits of the output of conventional unit i, respectively;

[0063] Flexible load constraints include interruptible load constraints and transferable load constraints; among them, considering the constraints on power outage capacity and frequency, the interruptible load constraints are as follows:

[0064]

[0065]

[0066] In the formula, P IL,j and These represent the minimum and maximum values ​​of the interruptible load j, respectively; N IL,j The maximum number of interruptible loads j within the scheduling cycle;

[0067] The total electricity consumption of transferable load remains constant within a scheduling cycle, and the constraints on the transferable load are as follows:

[0068]

[0069]

[0070]

[0071] In the formula, P SL,k,t The transferable load k represents the power consumption that was not won in the standby market at time t; P SL,k,t and These are the minimum and maximum values ​​of the transferable load k, respectively;

[0072] The line safety constraints are:

[0073]

[0074] In the formula, Ω B For the set of system branches; (·) T This is a matrix transpose operation; These are the injection transfer distribution factor vectors of the unit node and the load node to branch b, respectively; P is the injection transfer distribution factor of the tie-line power exchange node to branch b. t Let t be the output vector of all units; This represents the upper limit of power transmission for branch b.

[0075] The unit's ramp rate constraint is:

[0076]

[0077] Considering the standby market, the upper and lower limits of unit output are constrained:

[0078]

[0079]

[0080] In the formula, r i,t Let represent the upper or lower reserve capacity of generator unit i at time t.

[0081] Preferably, step S3 includes:

[0082] Step S31: Assume the electricity market adopts nodal marginal pricing and the reserve market adopts regional pricing. Based on the Caro-Kuhn-Tucker conditions, construct the extended Lagrangian function to obtain the dual multipliers for each constraint, and calculate the electricity and reserve market price at time t.

[0083]

[0084] L t,2 =l t,2

[0085] In the formula, L t,e,1 Let L be the marginal electricity price at node e at time t in the electricity market; t,2 The standby electricity price at time t; t,1 l t,2 These are the dual multipliers of the power balance constraint and the reserve demand constraint, respectively. These are the dual multipliers for the upper limit safety constraint of the branch and the dual multipliers for the lower limit safety constraint of the branch, respectively; K e,b Let be the power transfer factor from node e to branch b;

[0086] Step S32: Construct an uncertain set model and define the polyhedral uncertain variable set Ω. U With the set of uncertain errors Ω Z The expression is:

[0087]

[0088]

[0089] P t ∈[P t F -P t ^,P t F +Pt ^],P t ^ >0

[0090]

[0091] In the formula, The predicted value of the uncertain variable at time t. z represents the maximum prediction error of the uncertain variable at time t; t This indicates the degree of deviation between the actual value and the predicted value of the uncertain variable; Γ is the uncertainty parameter, reflecting the degree of influence of uncertainty on decision-making. When Γ = 0, the corresponding robust optimization model is a deterministic model.

[0092] Step S33, construct the robust optimization model, with the objective function as:

[0093] max(minf)

[0094] The constraints of the robust optimization model are:

[0095]

[0096]

[0097] In the formula, z w,t z represents the degree of deviation between actual wind power and wind power forecasts. n,t z represents the degree of deviation between actual photovoltaic (PV) values ​​and predicted PV values. l,e,t This represents the degree of deviation between the actual load and the predicted load. The maximum predicted error of the wind turbine w at time t; This represents the maximum prediction error of the output of photovoltaic unit n at time t. The maximum prediction error of the load at time t; the robust optimization model simultaneously executes all the constraints set above.

[0098] Preferably, step S4 includes:

[0099] Step S41: Set the system and operation parameters, solve the objective function of the robust optimization model, and obtain the optimal reserve capacity;

[0100] Step S42, in response to unit failure, performs an N-1 safety check on the system backup obtained in step S41, specifically: assuming the single-unit capacity of the maximum-capacity unit in the system is... like If the security check is satisfied, proceed to step S44; otherwise, proceed to step S43.

[0101] Step S43, the total system reserve capacity Rt Determined as Using CPLEX to solve the objective function minf', the total system reserve capacity is calculated. Re-clearing between generating units and flexible loads:

[0102]

[0103] The constraints on the objective function minf' are as follows:

[0104]

[0105] Step S44, in response to line faults, performs an N-1 safety check on the reserve capacity of each generating unit and flexible load, including:

[0106] Step S441, from the line set Ω B In the middle, select line b;

[0107] Step S442, modify the constraints to simulate line b fault. The modified constraints are as follows:

[0108]

[0109]

[0110]

[0111] In the formula, a b The variable is 0-1, indicating whether line b is switched. 0 means the line is switched, and 1 means it is not switched. |·| calculates the number of elements in the set. The subscripts fr(b) and to(b) represent the beginning and end of line b, respectively. The system has a power surplus at time t; f represents the system power deficit at time t; fr(b),t f to(b),t These represent the power flow injected into the system from the beginning and end of line b at time t under fault conditions; f b,t x represents the DC power flow of line b at time t under fault conditions; b Let θ be the reactance of line b; fr(b),t θ to(b),t These are the voltage phase angles at the beginning and end of line b at time t under the fault scenario, respectively.

[0112] Step S443: Traverse all routes and use a heuristic algorithm to optimize the objective function under the worst-case route failure scenario. If optimized and If the worst-case fault scenario line safety verification is passed, the verification process ends; otherwise, the total system reserve capacity is reset, and the system is re-cleared between the generating units and flexible loads according to the objective function minf' in step S43. The constraint condition for resetting the total system reserve capacity is:

[0113]

[0114]

[0115] Furthermore, the present invention provides a joint clearing system for electrical energy and standby service that considers safety verification, comprising:

[0116] The risk cost model building module is used to build risk cost models for insufficient upper and lower reserves in the system;

[0117] The joint clearing model building module establishes a joint clearing model for the electricity and reserve markets with the goal of minimizing operating costs, based on the aforementioned risk cost model.

[0118] The robust optimization model building module establishes a robust optimization model for the uncertainty of new energy output based on the joint clearing model of the electric energy and reserve market.

[0119] The N-1 safety verification module solves the robust optimization model to obtain the optimal reserve capacity and the optimal bid-winning reserve capacity of the system's reserve body. It then performs an N-1 safety verification on the optimal reserve capacity. For cases that do not meet the N-1 safety verification, the optimal reserve capacity is adjusted, and the adjusted and updated optimal reserve capacity is re-optimized and cleared to obtain the optimal bid-winning reserve capacity of the system's reserve body that meets the N-1 safety verification. The system's reserve body includes generating units and flexible loads. Flexible loads include interruptible loads and transferable loads. The optimal system reserve capacity is composed of the bid-winning reserve capacities of each generating unit and flexible load.

[0120] As can be seen from the above technical solution, the method and system for joint clearing of power and reserve services considering safety verification provided by the embodiments of the present invention first establishes a risk cost model for insufficient upper and lower reserves in the system; based on the risk cost model, a joint clearing model for the power and reserve market with the goal of minimizing operating costs is established; based on the joint clearing model for the power and reserve market, a robust optimization model is established to address the uncertainty of new energy output; by solving the robust optimization model, the optimal reserve capacity and the optimal winning bid reserve capacity of the system's reserve body are obtained; an N-1 safety verification is performed on the optimal reserve capacity; for cases that do not meet the N-1 safety verification, the optimal reserve capacity is adjusted, and the adjusted and updated optimal reserve capacity is re-optimized and cleared to obtain the optimal winning bid reserve capacity of the system's reserve body that meets the N-1 safety verification; the system's reserve body includes generating units and flexible loads, and flexible loads include interruptible loads and transferable loads; the optimal system reserve capacity is composed of the winning bid reserve capacity of each generating unit and flexible load. The present invention considers the risk cost of insufficient upper and lower reserves, ensuring the safe and reliable operation of the power system, while performing system N-1 safety verification for reserve capacity optimization oriented towards economic costs, reducing system safety hazards. Attached Figure Description

[0121] Figure 1 A flowchart for a method of jointly clearing electrical energy and standby services to take into account safety verification. Detailed Implementation

[0122] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0123] Taking into account factors such as flexible load characteristics, risks arising from insufficient upper and lower reserves, and net load uncertainty, a joint clearing model for the day-ahead energy and reserve ancillary service market, involving both generation and load, was established. Furthermore, a reserve capacity correction method incorporating N-1 safety checks was proposed. The specific steps are as follows:

[0124] Step S1: Establish a risk cost model for insufficient upper and lower reserves in the system;

[0125] Step S2: Based on the risk-cost model, establish a joint clearing model for the electricity and standby markets with the goal of minimizing operating costs;

[0126] Step S3: Based on the joint clearing model of the electric energy and reserve market, establish a robust optimization model to address the uncertainty of new energy output.

[0127] Step S4: Solve the robust optimization model to obtain the optimal reserve capacity and the optimal bid reserve capacity of the system's reserve body. Perform an N-1 safety check on the optimal reserve capacity. If the N-1 safety check is not met, adjust the optimal reserve capacity and re-optimize and clear the updated optimal reserve capacity to obtain the optimal bid reserve capacity of the system's reserve body that meets the N-1 safety check. The system's reserve body includes generating units and flexible loads. Flexible loads include interruptible loads and transferable loads. The optimal reserve capacity of the system is composed of the bid reserve capacity of each generating unit and flexible load.

[0128] The risk-cost model expression is:

[0129]

[0130] In the formula, A(R) t (This refers to risk costs.) The cost of backup risk caused by insufficient backup in the system. R represents the down-reserve risk cost caused by insufficient down-reserve in the system. t This represents the total system reserve capacity.

[0131] Backup risk cost The cost of load loss caused by unit failures and net load forecasting errors is expressed as:

[0132]

[0133] In the formula, C represents the system's upper reserve capacity at time t; L Cost per unit of load loss; Let be the expected value of the system's reserve deficit at time t. The expression is:

[0134]

[0135]

[0136]

[0137]

[0138] In the formula, PR G,i,t Let PR be the probability of unit i failing at time t; i,t Let PR be the probability of unit i failing at time t; y,t Let Ω be the probability of unit y failing at time t; GFor all units; Represents the system's reserve deficit; Ω IL Ω SL These are interruptible and transferable load sets, respectively; P i,t Let i be the amount of wastewater discharged from unit i at time t. The reserve capacity of conventional unit i at time t; These represent the standby capacity of interruptible load j and transferable load k at time t, respectively; δ D,t Let be the net load forecast error at time t, which follows a mean of 0 and a standard deviation of σ. D,t The normal distribution of , where:

[0139]

[0140]

[0141]

[0142] In the formula, P D,t The actual net load value at time t. Let t be the predicted net load value at time t; t∈Ω T Ω T For statistical time sets;

[0143] Lowering the risk cost of backup The expression is:

[0144]

[0145] In the formula, C represents the system's reserve capacity at time t; G Cost of decommissioning a unit of generating capacity; Let be the expected value of the reserve deficit in the system at time t. The expression is:

[0146]

[0147] PR L,t =q C / (q C +q L (12)

[0148]

[0149]

[0150]

[0151]

[0152] In the formula, the probability of unplanned system outage PR L,t q is the ratio of the cumulative power outages caused by factors other than unit failures to the total power demand within the historical observation period of the month in which time t is located; c q L These represent the cumulative power outage and power supply during the historical observation period of the month in which time t is located; For backup shortages in the system; P L,t Let ε be the load vector of all nodes at time t; L,t The average percentage of out-of-service load when unplanned outages occur at time t; The reserve capacity of the transferable load k at time t; These represent the load outage power, load demand, and percentage of unplanned load outages at time t within the historical observation period, excluding unit failures, during the xth unplanned load outage. N represents the cumulative number of load outages at time t within the historical observation period. P represents the reserve capacity of conventional unit i at time t. SL,k,t q represents the winning bid power at time t for transferable load k in the electricity market; Δt is the statistical time interval; q SL,k Let k be the total electricity demand of the transferable load during the scheduling period.

[0153] Preferably, the objective function of the joint clearing model for the electricity and reserve markets, which aims to minimize operating costs, is:

[0154]

[0155] In the formula, C(P) i,t Let be the power generation cost quotation function for conventional unit i at time t; and These are the bid-winning status variables for the reserve capacity of conventional unit i at time t and the bid-winning status variables for the reserve capacity at time t, respectively. A value of 1 indicates that the bid has been won and a value of 0 indicates that the bid has not been won. These are the bidding functions for conventional unit i in the upper reserve market and the bidding functions for conventional unit i in the lower reserve market, respectively. Let j be the bidding function for interruptible load j in the upper standby market; These are the bid functions for the transferable load k in the upper and lower standby markets, respectively; S i The startup cost of conventional unit i; Let i be the start / stop state variable of a conventional unit i at time t. A value of 1 indicates power-on, and a value of 0 indicates power-off; u IL,j,t Let u be the state variable of the interruptible load j at time t. IL,j,t A value of 1 indicates that the interruptible function is enabled, and a value of 0 indicates that the interruptible function is not enabled. and These are the bidding status variables of the transferable load k at time t, representing the reserve capacity at the beginning and end of the bidding process. A value of 1 indicates that the bid has been won, and a value of 0 indicates that the bid has not been won.

[0156] The power generation cost C(P) of conventional generating units i,t ), Quotation function for the backup market Quotation function for the next standby market The expressions are as follows:

[0157]

[0158]

[0159]

[0160] In the formula, a i,1 a i,2 a i,3 These are the bidding coefficients for conventional unit i in the electricity market; m i,1 m i,2 m i,3 These are the standby bid coefficients for conventional unit i in the standby market; m′ i,1 m′ i,2 m′ i,3 These are the standby bid coefficients for conventional unit i in the standby market;

[0161] In the standby market, the standby bid function for interruptible loads. and the standby quotation function for transferable loads They are respectively:

[0162]

[0163]

[0164] In the formula, g i,1 g i,2 g i,3 These represent the standby bid coefficients for interruptible load j in the standby market; g k,1 g k,2 g k,3 These are the standby bid coefficients for transferable load k in the standby market;

[0165] The standby bid function for transferable load in the standby market is:

[0166]

[0167] In the formula, g' k,1 g' k,2g' k,3 These are the standby bid coefficients for transferable load k in the standby market;

[0168] The constraints for the joint clearing of spot market electricity and reserve market include system power balance, minimum start-up and shutdown time constraints for conventional units, reserve capacity constraints for conventional units, flexible load constraints, line safety constraints, unit ramp rate constraints, and upper and lower limits of unit output after considering the reserve market.

[0169] The system power balance constraint is:

[0170]

[0171] In the formula, Ω W A collection of wind turbine units; Ω is the predicted output value of the wind turbine w at time t; PV A collection of photovoltaic units; Ω is the predicted output value of photovoltaic unit n at time t. E For the system node set; P represents the predicted load on node e at time t. DC,t The total power of all inter-provincial connection lines at time t, with outgoing power being positive and incoming power being negative;

[0172] The minimum start-up and shutdown time constraints for conventional generating units are:

[0173]

[0174] In the formula, , respectively, represent the minimum continuous start-up time and minimum continuous downtime of conventional unit i; m is the time point;

[0175] The conventional unit standby capacity constraint is:

[0176]

[0177]

[0178] In the formula, τ is the ramp rate of conventional unit i; τ is the response time of the standby capacity. For conventional unit i, the downhill ramp rate is... and P i These are the upper and lower limits of the output of conventional unit i, respectively;

[0179] Flexible load constraints include interruptible load constraints and transferable load constraints; among them, considering the capacity and frequency of power outages, the interruptible load constraint is as follows:

[0180]

[0181]

[0182] In the formula, P IL,j and These represent the minimum and maximum values ​​of the interruptible load j, respectively; N IL,j The maximum number of interruptible loads j within the scheduling cycle;

[0183] The total electricity consumption of transferable load remains constant within a dispatch cycle, and the constraints on transferable load are:

[0184]

[0185]

[0186]

[0187] In the formula, P SL,k,t The transferable load k represents the power consumption that was not won in the standby market at time t; P SL,k,t and These are the minimum and maximum values ​​of the transferable load k, respectively;

[0188] The line safety constraints are:

[0189]

[0190] In the formula, Ω B For the set of system branches; (·) T This is a matrix transpose operation; These are the injection transfer distribution factor vectors of the unit node and the load node to branch b, respectively; P is the injection transfer distribution factor of the tie-line power exchange node to branch b. t Let t be the output vector of all units; This represents the upper limit of power transmission for branch b.

[0191] The unit's ramp rate constraint is:

[0192]

[0193] Considering the standby market, the upper and lower limits of unit output are constrained:

[0194]

[0195]

[0196] In the formula, r i,t Let represent the upper or lower reserve capacity of generator unit i at time t.

[0197] Preferably, step S3 includes:

[0198] Step S31: Assume the electricity market adopts nodal marginal pricing and the reserve market adopts regional pricing. Based on the Caro-Kuhn-Tucker conditions, construct the extended Lagrangian function to obtain the dual multipliers for each constraint, and calculate the electricity and reserve market price at time t.

[0199]

[0200] L t,2 =l t,2 (37)

[0201] In the formula, L t,e,1 Let L be the marginal electricity price at node e at time t in the electricity market; t,2 The standby electricity price at time t; t,1 l t,2 These are the dual multipliers of the power balance constraint and the reserve demand constraint, respectively. These are the dual multipliers for the upper limit safety constraint of the branch and the dual multipliers for the lower limit safety constraint of the branch, respectively; K e,b Let be the power transfer factor from node e to branch b;

[0202] Step S32: Construct an uncertain set model and define the polyhedral uncertain variable set Ω. U With the set of uncertain errors Ω Z The expression is:

[0203] Ω U ={P t |P t =P t F +P t ^z t ,t∈Ω T} (38)

[0204]

[0205] P t ∈[P t F -P t ^,P t F +P t ^],P t ^ >0 (40)

[0206]

[0207] In the formula, The predicted value of the uncertain variable at time t. z represents the maximum prediction error of the uncertain variable at time t; t This indicates the degree of deviation between the actual value and the predicted value of the uncertain variable; Γ is the uncertainty parameter, reflecting the degree of influence of uncertainty on decision-making. When Γ = 0, the corresponding robust optimization model is a deterministic model.

[0208] Step S33, construct a robust optimization model, with the objective function as follows:

[0209] max(minf) (42)

[0210] The constraints of the robust optimization model are:

[0211]

[0212]

[0213] In the formula, z w,t z represents the degree of deviation between actual wind power and wind power forecasts. n,t z represents the degree of deviation between actual photovoltaic (PV) values ​​and predicted PV values. l,e,t This represents the degree of deviation between the actual load and the predicted load. The maximum predicted error of the wind turbine w at time t; This represents the maximum prediction error of the output of photovoltaic unit n at time t. The maximum prediction error of the load at time t; the robust optimization model simultaneously executes all the constraints set above.

[0214] Preferably, step S4 includes:

[0215] Step S41: Set the system and operation parameters, solve the objective function of the robust optimization model, and obtain the optimal reserve capacity;

[0216] Step S42, in response to unit failure, performs an N-1 safety check on the system backup obtained in step S41. Specifically, assume the single-unit capacity of the unit with the maximum operating capacity of the system is... like If the security check is satisfied, proceed to step S44; otherwise, proceed to step S43.

[0217] Step S43, the total system reserve capacity R t Determined as Using CPLEX to solve the objective function minf', the total system reserve capacity is calculated. Re-clearing between generating units and flexible loads:

[0218]

[0219] The constraints on the objective function minf' are as follows:

[0220]

[0221] Step S44, in response to line faults, performs an N-1 safety check on the reserve capacity of each generating unit and flexible load, including:

[0222] Step S441, from the line set Ω B In the middle, select line b;

[0223] Step S442, modify the constraints to simulate line b fault. The modified constraints are as follows:

[0224]

[0225]

[0226]

[0227] In the formula, a b The variable is 0-1, indicating whether line b is switched. 0 means the line is switched, and 1 means it is not switched. |·| calculates the number of elements in the set. The subscripts fr(b) and to(b) represent the beginning and end of line b, respectively. The system has a power surplus at time t; f represents the system power deficit at time t; fr(b),t f to(b),t These represent the power flow injected into the system from the beginning and end of line b at time t under fault conditions; f b,t x represents the DC power flow of line b at time t under fault conditions; b Let θ be the reactance of line b; fr(b),t θ to(b),t These are the voltage phase angles at the beginning and end of line b at time t under the fault scenario, respectively.

[0228] Step S443: Traverse all routes and use a heuristic algorithm to optimize the objective function under the worst-case route failure scenario. If optimized and If the worst-case line safety verification is passed, the verification process ends; otherwise, the total system reserve capacity is reset, and the system is re-cleared between the generating units and flexible loads according to the objective function minf' in step S43. The constraint condition for resetting the total system reserve capacity is:

[0229]

[0230]

[0231] Furthermore, the present invention provides a joint clearing system for electrical energy and standby service that considers safety verification, for performing... Figure 1 The method is shown. The system includes:

[0232] The risk cost model building module is used to build risk cost models for insufficient upper and lower reserves in the system;

[0233] The joint clearing model building module, based on the risk-cost model, establishes a joint clearing model for the electricity and reserve markets with the goal of minimizing operating costs;

[0234] The robust optimization model building module, based on the joint clearing model of the power and reserve markets, establishes a robust optimization model to address the uncertainty of new energy output.

[0235] The N-1 safety verification module solves the robust optimization model to obtain the optimal reserve capacity and the optimal bid-winning reserve capacity of the system's reserve body. It then performs an N-1 safety verification on the optimal reserve capacity. For cases that do not meet the N-1 safety verification, the optimal reserve capacity is adjusted, and the adjusted and updated optimal reserve capacity is re-optimized and cleared to obtain the optimal bid-winning reserve capacity of the system's reserve body that meets the N-1 safety verification. The system's reserve body includes generating units and flexible loads. Flexible loads include interruptible loads and transferable loads. The optimal system reserve capacity is composed of the bid-winning reserve capacity of each generating unit and flexible load.

[0236] The risk cost model expression is as follows:

[0237]

[0238] Backup risk cost The cost of load loss caused by unit failures and net load forecasting errors is expressed as:

[0239]

[0240] Lowering the risk cost of backup The expression is:

[0241]

[0242] The objective function of the joint clearing model for the electricity and reserve markets, which aims to minimize operating costs, is:

[0243]

[0244] The constraints for the joint clearing of spot market electricity and reserve market include system power balance, minimum start-up and shutdown time constraints for conventional units, reserve capacity constraints for conventional units, flexible load constraints, line safety constraints, unit ramp rate constraints, and upper and lower limits of unit output after considering the reserve market.

[0245] The system power balance constraint is:

[0246]

[0247] The minimum start-up and shutdown time constraints for conventional generating units are:

[0248]

[0249] The conventional unit standby capacity constraint is:

[0250]

[0251]

[0252] Flexible load constraints include interruptible load constraints and transferable load constraints; among them, considering the constraints on power outage capacity and frequency, the interruptible load constraints are as follows:

[0253]

[0254]

[0255] The total electricity consumption of transferable load remains constant within a scheduling cycle, and the constraints on the transferable load are as follows:

[0256]

[0257]

[0258]

[0259] The line safety constraints are:

[0260]

[0261] The unit's ramp rate constraint is:

[0262]

[0263] After considering the standby market, the upper and lower limits of unit output are constrained as follows:

[0264]

[0265]

[0266] The robust optimization model building module is used for:

[0267] Assuming the electricity market adopts nodal marginal pricing and the reserve market adopts regional pricing, based on the Caro-Kuhn-Tucker conditions, an extended Lagrangian function is constructed to obtain the dual multipliers for each constraint. The electricity and reserve market price at time t are then calculated.

[0268]

[0269] L t,2 =l t,2

[0270] Construct an uncertain set model and define a polyhedral set of uncertain variables Ω. U With the set of uncertain errors Ω Z The expression is:

[0271] Ω U ={P t |P t =P t F +P t ^z t ,t∈Ω T}

[0272]

[0273] P t ∈[P t F -P t ^,P t F +P t ^],P t ^ >0

[0274]

[0275] Construct the robust optimization model, with the objective function as follows:

[0276] max(minf)

[0277] The constraints of the robust optimization model are:

[0278]

[0279]

[0280] The N-1 security verification module is used for:

[0281] By setting the system and computational parameters, the objective function of the robust optimization model is solved to obtain the optimal reserve capacity;

[0282] In the event of a unit failure, an N-1 safety check is performed on the optimal reserve capacity, specifically as follows:

[0283] Assume the single-unit capacity of the maximum capacity unit in the system is . like If the security check is satisfied, the process of performing the N-1 security check includes:

[0284] First, let's start with the line set Ω B In the middle, select line b;

[0285] The constraints have been modified to simulate a fault on line b. The modified constraints are as follows:

[0286]

[0287]

[0288]

[0289] Traverse all routes and use a heuristic algorithm to optimize the objective function under the worst-case route failure scenario. If optimized and If the worst-case line safety verification is passed, the verification process ends; otherwise, the total system reserve capacity is reset, and the system is re-cleared between generating units and flexible loads according to the objective function minf'. The constraint for resetting the total system reserve capacity is as follows:

[0290]

[0291]

[0292] In addition, if If the security check is not met, then the total system backup capacity R will be reduced. t Determined as Using CPLEX to solve the objective function minf', the total system reserve capacity is calculated. Re-clearing between generating units and flexible loads:

[0293]

[0294] The constraints on the objective function minf' are as follows:

[0295]

[0296] This invention relates to factors such as flexible load characteristics, risks arising from insufficient upper and lower reserves, and net load uncertainty, and in particular, establishes a joint clearing model for the day-ahead energy and reserve ancillary services market involving both generation and load. Compared to existing technologies, the advantages of this invention are:

[0297] (1) Compared with the existing technology, which does not adequately consider the impact of uncertain factors such as random system failures, load and new energy output prediction errors, this invention considers the risk cost when the upper and lower reserves are insufficient, thus ensuring the safe and reliable operation of the power system.

[0298] (2) Compared with the limited research on the coupling of the power market and the ancillary services market in the existing technology, this invention establishes a day-ahead joint clearing model for the power market and the standby market, taking into account the impact of both markets.

[0299] (3) Compared with the prior art, which ignores the security verification of backup capacity, the present invention performs system N-1 security verification for backup capacity optimization with economic cost, thereby reducing system security risks.

[0300] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of the invention. Those skilled in the art will understand that implementing all or part of the above-described embodiments and making equivalent changes in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A method for joint clearing of electrical energy and standby service considering safety verification, characterized in that, include: Step S1: Establish a risk cost model for insufficient upper and lower reserves in the system; Step S2: Based on the risk cost model, establish a joint clearing model for the electricity and standby markets with the goal of minimizing operating costs; Step S3: Based on the joint clearing model of the power and reserve markets, establish a robust optimization model to address the uncertainty of new energy output. ; Step S4: Solve the robust optimization model to obtain the optimal reserve capacity and the optimal bid reserve capacity of the system's reserve main body. The objective function minf is: ; In the formula, Ω G For all units; Ω T For statistical time sets; Ω IL Ω SL These are interruptible and transferable load sets, respectively; C(P) i,t Let be the power generation cost quotation function for conventional unit i at time t; and These are the bid-winning status variables for the reserve capacity of conventional unit i at time t and the bid-winning status variables for the reserve capacity at time t, respectively. A value of 1 indicates that the bid has been won and a value of 0 indicates that the bid has not been won. , These are the bidding functions for conventional unit i in the upper reserve market and the bidding functions for conventional unit i in the lower reserve market, respectively. Let j be the bidding function for interruptible load j in the upper standby market; , These are the bid functions for the transferable load k in the upper and lower standby markets, respectively; S i The startup cost of conventional unit i; Let i be the start / stop state variable of a conventional unit i at time t. A value of 1 indicates power on, and a value of 0 indicates power off; Let j be the state variable of the interruptible load at time t. A value of 1 indicates that the interruptible function is enabled, and a value of 0 indicates that the interruptible function is not enabled. and These are the bidding status variables of the transferable load k at time t, representing the reserve capacity at the beginning and end of the bidding process. A value of 1 indicates that the bid has been won, and a value of 0 indicates that the bid has not been won. For risk costs; The constraints used in the robust optimization model include system power balance, minimum start-up and shutdown time constraints for conventional units, reserve capacity constraints for conventional units, flexible load constraints, line safety constraints, unit ramp rate constraints, and upper and lower limits of unit output after considering the reserve market. Perform an N-1 security check on the optimal reserve capacity. If the N-1 security check is not met, reduce the total system reserve capacity R. t Adjust to the single unit capacity of the set maximum system operating capacity. Using the objective function The total system reserve capacity A re-clearing process is performed between generating units and flexible loads to obtain the optimal reserve capacity of the system's main reserve that meets the N-1 safety check: ; The system's backup main body includes generating units and flexible loads. Flexible loads include interruptible loads and transferable loads. The system's optimal backup capacity is composed of the backup capacity won by each generating unit and flexible load. Step S4 includes: Step S41: Set the system and operation parameters, solve the objective function of the robust optimization model, and obtain the optimal reserve capacity; Step S42, in response to unit failure, performs an N-1 safety check on the system backup obtained in step S41, specifically: assuming the single-unit capacity of the maximum-capacity unit in the system is... , Let t be the system's upper reserve capacity. > If the security check is satisfied, proceed to step S44; otherwise, proceed to step S43. Step S43, the total system reserve capacity R t Determined as Solving the objective function using CPLEX Total system reserve capacity A re-clearing process is performed between generating units and flexible loads; where the objective function is... The constraints are: ; In the formula, The reserve capacity of conventional unit i at time t; , These are the standby capacities of interruptible load j and transferable load k at time t, respectively. Step S44, in response to line faults, performs an N-1 safety check on the reserve capacity of each generating unit and flexible load, including: Step S441, from the line set Ω B In the middle, select line b; Step S442, modify the constraints to simulate line b fault. The modified constraints are as follows: ; ; ; In the formula, a b It is a 0-1 variable, indicating whether line b is switched on or off. A value of 0 indicates that the line is switched off, and a value of 1 indicates that it is not switched off. Calculate the number of elements in a set; P i,t Ω represents the clearing volume of unit i at time t. W A collection of wind turbine units; Ω is the predicted output value of the wind turbine w at time t; PV A collection of photovoltaic units; Ω is the predicted output value of photovoltaic unit n at time t. E For the system node set; This represents the predicted load of node e at time t; the subscript... , These represent the beginning and end of line b, respectively. The system has a power surplus at time t; f represents the system power deficit at time t; fr(b),t f to(b),t These represent the power flow injected into the system from the beginning and end of line b at time t under fault conditions; δ D,t P represents the net load prediction error at time t. DC,t f is the total power of all inter-provincial connecting lines at time t; b,t x represents the DC power flow of line b at time t under fault conditions; b Let θ be the reactance of line b; fr(b),t θ to(b),t These are the voltage phase angles at the beginning and end of line b at time t under the fault scenario, respectively. Step S443: Traverse all routes and use a heuristic algorithm to optimize the objective function under the worst-case route failure scenario. If optimization yields < and < If the worst-case fault scenario line safety check is passed, the check process ends. Set the system's reserve capacity at time t; otherwise, reset the system's total reserve capacity and then proceed according to the objective function in step S43. A re-clearing process is performed between generating units and flexible loads, with the constraint of resetting the total system reserve capacity as follows: ; ; In the formula, The reserve capacity of the transferable load k at time t; This represents the reserve capacity of conventional unit i at time t.

2. The method for joint clearing of electrical energy and standby service considering safety verification as described in claim 1, characterized in that, The risk cost The model expression is: ; In the formula, The cost of backup risk caused by insufficient backup in the system. R represents the down-reserve risk cost caused by insufficient down-reserve in the system. t This represents the total system reserve capacity. The above backup risk cost The cost of load loss caused by unit failures and net load forecasting errors is expressed as: ; In the formula, C represents the system's upper reserve capacity at time t; L Cost per unit of load loss; Let be the expected value of the system's reserve deficit at time t. The expression is: ; ; ; ; In the formula, PR G,i,t Let PR be the probability of unit i failing at time t; i,t Let PR be the probability of unit i failing at time t; y,t Let Ω be the probability of unit y failing at time t; G For all units; Represents the system's reserve deficit; Ω IL Ω SL These are interruptible and transferable load sets, respectively; P i,t Let i be the amount of wastewater discharged from unit i at time t. The reserve capacity of conventional unit i at time t; , These represent the standby capacity of interruptible load j and transferable load k at time t, respectively; δ D,t Let be the net load forecast error at time t, which follows a mean of 0 and a standard deviation of σ. D,t The normal distribution of , where: ; ; ; In the formula, P D,t The actual net load value at time t. Let t be the predicted net load value at time t; t∈Ω T ; The following backup risk cost The expression is: ; In the formula, C G Cost of decommissioning a unit of generating capacity; Let be the expected value of the reserve deficit in the system at time t. The expression is: ; ; ; ; ; ; In the formula, the probability of unplanned system outage PR L,t q is the ratio of the cumulative power outages caused by factors other than unit failures to the total power demand within the historical observation period of the month in which time t is located; c q L These represent the cumulative power outage and power supply during the historical observation period of the month in which time t is located; For backup shortages in the system; P L,t Let ε be the load vector of all nodes at time t; L,t The average percentage of out-of-service load when unplanned outages occur at time t; The reserve capacity of the transferable load k at time t; , , , , respectively, represent the load outage power, load demand, and percentage of unplanned load outages at time t within the historical observation period, when an unplanned load outage occurs for the xth time due to reasons other than unit failure; N represents the cumulative number of load outages at time t within the historical observation period; P represents the reserve capacity of conventional unit i at time t. SL,k,t q represents the winning bid power at time t for transferable load k in the electricity market; Δt is the statistical time interval; q SL,k Let k be the total electricity demand of the transferable load during the scheduling period.

3. The method for joint clearing of electrical energy and standby service considering safety verification as described in claim 2, characterized in that, The power generation cost C(P) of conventional generating units i,t ), Quotation function for the backup market Quotation function for the backup market The expressions are as follows: ; ; ; In the formula, a i,1 a i,2 a i,3 These are the bidding coefficients for conventional unit i in the electricity market; m i,1 m i,2 m i,3 These are the standby bid coefficients for conventional unit i in the standby market; , , These are the standby bid coefficients for conventional unit i in the standby market; In the standby market, the standby bid function for interruptible loads. and the standby quotation function for transferable loads They are respectively: ; ; In the formula, g i,1 g i,2 g i,3 These are the standby bid coefficients for interruptible load j in the standby market; , , These are the standby bid coefficients for transferable load k in the standby market; The standby bid function for transferable load in the standby market is: ; In the formula, , , These are the standby bid coefficients for transferable load k in the standby market; The constraints for the joint clearing of spot market electricity and reserve market include system power balance, minimum start-up and shutdown time constraints for conventional units, reserve capacity constraints for conventional units, flexible load constraints, line safety constraints, unit ramp rate constraints, and upper and lower limits of unit output after considering the reserve market. The system power balance constraint is: ; In the formula, Ω W A collection of wind turbine units; Ω is the predicted output value of the wind turbine w at time t; PV A collection of photovoltaic units; Ω is the predicted output value of photovoltaic unit n at time t. E For the system node set; P represents the predicted load on node e at time t. DC,t The total power of all inter-provincial connection lines at time t, with outgoing power being positive and incoming power being negative; The minimum start-up and shutdown time constraints for conventional generating units are: ; In the formula, , , respectively, represent the minimum continuous start-up time and minimum continuous downtime of conventional unit i; m is the time point; The conventional unit standby capacity constraint is: ; ; In the formula, For conventional unit i, the rate of ascent is [missing information]. The response time for backup capacity; For conventional unit i, the downhill ramp rate is... and These are the upper and lower limits of the output of conventional unit i, respectively; Flexible load constraints include interruptible load constraints and transferable load constraints; among them, considering the constraints on power outage capacity and frequency, the interruptible load constraints are as follows: ; ; In the formula, and These represent the minimum and maximum values ​​of the interruptible load j, respectively; N IL,j The maximum number of interruptible loads j within the scheduling cycle; The total electricity consumption of transferable load remains constant within a scheduling cycle, and the constraints on the transferable load are as follows: ； ; ; In the formula, P SL,k,t The transferable load k represents the power consumption that was not won in the standby market at time t; and These are the minimum and maximum values ​​of the transferable load k, respectively; The line safety constraints are: ; In the formula, Ω B For the set of system branches; (·) T This is a matrix transpose operation; , These are the injection transfer distribution factor vectors of the unit node and the load node to branch b, respectively; P is the injection transfer distribution factor of the tie-line power exchange node to branch b. t Let t be the output vector of all units; This represents the upper limit of power transmission for branch b. The unit's ramp rate constraint is: ; Considering the standby market, the upper and lower limits of unit output are constrained: ; ; In the formula, Let represent the upper or lower reserve capacity of generator unit i at time t.

4. The method for joint clearing of electrical energy and standby service considering safety verification as described in claim 3, characterized in that, Step S3 includes: Step S31: Assume the electricity market adopts nodal marginal pricing and the reserve market adopts regional pricing. Based on the Caro-Kuhn-Tucker conditions, construct the extended Lagrangian function to obtain the dual multipliers for each constraint, and calculate the electricity and reserve market price at time t. ; ; In the formula, L t,e,1 Let L be the marginal electricity price at node e at time t in the electricity market; t,2 The standby electricity price at time t; t,1 l t,2 These are the dual multipliers of the power balance constraint and the reserve demand constraint, respectively. , These are the dual multipliers for the upper limit safety constraint of the branch and the dual multipliers for the lower limit safety constraint of the branch, respectively; K e,b Let be the power transfer factor from node e to branch b; Step S32: Construct an uncertain set model and define the polyhedral uncertain variable set Ω. U With the set of uncertain errors Ω Z The expression is: ; ; ; ; In the formula, The predicted value of the uncertain variable at time t. z represents the maximum prediction error of the uncertain variable at time t; t This indicates the degree of deviation between the actual value and the predicted value of the uncertain variable; Γ is the uncertainty parameter, reflecting the degree of influence of uncertainty on decision-making. The robust optimization model corresponding to this time is a deterministic model; Step S33, construct the objective function of the robust optimization model as follows: The constraints are: ; ; In the formula, z w,t z represents the degree of deviation between actual wind power and wind power forecasts. n,t z represents the degree of deviation between actual photovoltaic (PV) values ​​and predicted PV values. l,e,t This represents the degree of deviation between the actual load and the predicted load. The maximum predicted error of the wind turbine w at time t; This represents the maximum prediction error of the output of photovoltaic unit n at time t. This represents the maximum prediction error of the load at time t.

5. A joint clearing system for electrical energy and standby service considering safety verification, characterized in that, Used to perform the method according to any one of claims 1-4.

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