CN112909933A - Intraday rolling optimization scheduling method containing pumped storage unit under spot market environment - Google Patents
Intraday rolling optimization scheduling method containing pumped storage unit under spot market environment Download PDFInfo
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Abstract
The intraday rolling optimization scheduling method for the pumped storage unit under the spot market environment comprises the steps of designing an organization process of the intraday spot market transaction; acquiring basic data of the operation of the power system; establishing a day-interior rolling optimization scheduling model containing a pumped storage unit; carrying out linear processing on the electric quantity price piecewise function declared by each market subject; solving the intraday rolling model; and obtaining a unit correction plan operation curve of a rolling period in each day. The invention realizes the scheduling of the pumped storage unit according to the requirement while ensuring the complete consumption of new energy, and can simultaneously process the problems of following a power generation plan, sectional quotation of a power generation and utilization main body and the like.
Description
Technical Field
The invention relates to the field of power generation dispatching of a power system, in particular to a intraday rolling optimization dispatching method for researching a pumped storage unit under a spot market environment.
Background
Under the existing power grid regulation and control system, the dispatching operation of the pumped storage power station is dispatched according to needs by a power grid regulation and control center, the pumped storage power station is in a hot standby state all the time, and operation management personnel also need to be in a standby state for 24 hours, so that the labor intensity of personnel and the operation cost of equipment are increased, and the whole benefit of the pumped storage power station is not improved. Meanwhile, due to the influence of new energy output prediction and load prediction levels, the deviation between the current market and the real-time market clearing result is increased, more complete day-to-day market participation is needed, and the adjustment burden of the real-time market is reduced. Most of research works on coordination optimization scheduling strategies of the pumped storage unit participating in the thermal power/renewable energy power system are mainly theoretical research, so that the intraday rolling optimization operation method and the strategy of the pumped storage unit meeting the practical application requirements in the power market environment need to be deeply researched, and the power generation plan can be made to follow the day ahead.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a daily optimization scheduling method for researching a pumped storage unit under a spot market environment, and the method solves the problems that the income obtained by the existing pumped storage power station is difficult to cover investment and operation cost, the calling enthusiasm of a power grid is not high, meanwhile, the output prediction and load prediction level of new energy is limited, the following effect of a power generation plan formulated in the day before is not ideal when the system is actually operated, a market mechanism is introduced, and on the basis of a designed daily market trading flow, the daily electric quantity output plan is based. And (3) constructing a day-in rolling optimization scheduling model containing the pumped storage unit by using more accurate new energy output and load ultra-short term prediction (15min) information, carrying out linear processing on the electric quantity price information declared by a relevant market main body, and making a planned operation curve of the unit in one transaction period (4 h). The rolling deviation limit is designed, effective following of the day-ahead plan is guaranteed, and the adjusting cost of real-time scheduling is reduced. On the premise of meeting the power demand, the safe and stable operation of a power grid is guaranteed, and the development and consumption of renewable energy sources are promoted.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the intraday rolling optimization scheduling method for the pumped storage unit under the spot market environment is characterized by comprising the following steps of:
step one, designing a spot-shipment transaction process in the day;
acquiring basic data of the power system;
step three, establishing an intraday rolling optimization model containing a pumped storage unit;
step four, carrying out linear processing on the electric quantity price piecewise function declared by each market subject;
and step five, solving the rolling optimization model in the day to obtain a unit plan operation curve in the trading period.
In the first step, the intra-day spot market trading process comprises three stages of trading preparation, market clearing, trading information release and execution.
In the second step, the basic data includes a schedule issued by a thermal power generating unit 96 before the day with 15min as a point, operation state information, thermal power generating unit information, new energy station information, pumped storage power station information, regional load prediction information, and electric quantity price information declared by a market main body of a daily market.
In the third step, the objective function of the intraday rolling optimization model containing the pumped storage unit is established as follows:
wherein, Pi,tA force value is planned for the thermal power generating unit i in the day of the time period t,
for increasing or decreasing the power of the thermal power generating unit i in the time period t, Fi,tA force value is output for the new energy station i within the day of the time period t,
for increasing and decreasing the power of the new energy station i in the time period t,
increasing and decreasing force P of the pumped storage unit i in the power generation state in a time period tg,i,tA force value is planned for the pumped storage unit i to clearly output in the day of the time period t in the power generation state, the increase and decrease output of the unit at a certain moment can be expressed by utilizing the difference value between the day-ahead planned plan and the day-in planned plan of the unit, and Ci,t(Pi,t)、Ci,t(Fi,t)、Ci,t(Pg,i,t) Is a multi-section linear function related to the output intervals and the corresponding energy prices reported by the thermal power generating unit i, the new energy station i and the pumped storage unit i,
the state variable for generating the pumped storage unit, wherein 1 is a power generation state, 0 is a shutdown state, and N isGNumber of thermal power units of system, NMNumber of new energy stations for the system, NHFor number of pumped storage groups, T1Is a clearing period of 16 points in a trading cycle in one day.
In the third step, the constraint conditions of the built model include: the system comprises a system power balance constraint, a unit output constraint, a thermal power unit climbing constraint, a system rotation standby constraint, a pumped storage unit power generation constraint, a reservoir capacity balance constraint and a rolling planned value deviation constraint.
1) The expression of the above system power balance constraint is:
in the formula Pl,i,tFor the pumping power of the pumped-storage group i in the time period t,
state variables for pumping water of the pumped storage unit; 1 is a pumping state, 0 is a shutdown state, Lin,t、Loff,tRespectively is a certain regional load ultra-short term predicted value and an outsourcing power plan value of the transaction time interval t.
2) The expression of the unit output constraint is as follows:
Ii,t*Pi min≤Pi,t≤Ii,t*Pi max
Fi,t≤Qi,t
in the formula Pi max、Pi minThe upper and lower output limits Q of the thermal power generating unit ii,tPredicting the maximum output of the new energy station i in the time period t; i isi,tStarting and stopping state variables of the thermal power generating unit i in a time period t; 0 is a shutdown state, and 1 is an operation state; determined by a day-ahead plan.
3) The climbing constraint expression of the thermal power generating unit is as follows:
Pi,t-Pi,t-1≤△Pi U
Pi,t-1-Pi,t≤△Pi D
△Pi U、△Pi Dand the maximum up-down climbing speed of the thermal power generating unit i is obtained.
4) The expression of the above system rotation reserve constraint is:
in the formula Iu％、ld% load higher or lower than expected, fu％、fd% is the new energy yield above and below the expected percentage.
5) In the rolling optimization scheduling stage in the daytime, the pumped storage unit is mainly used for balancing the new energy output prediction error, so that the output, the storage capacity and the like of a pumped storage power station need to be constrained:
5.1) the pumped storage unit pumps water at full power, and only considering the output constraint of the unit during power generation, wherein the constraint expression is as follows:
in the formula
The maximum output is the maximum output of the pumped storage unit i during power generation;
5.2) the expression of reservoir capacity constraint is:
Emin≤Et≤Emax
in the formula EtFor the reservoir capacity of pumped storage power stations in time t, measured by the electric quantity, Emax、EminThe maximum and minimum storage capacities of the upper reservoir of the pumped storage power station are set;
5.3) the expression of the reservoir capacity balance constraint is:
in the formula etal、ηgThe water pumping and power generation efficiency of the water pumping and energy storage unit is improved;
5.4) the pumped storage unit can not generate power and pump water simultaneously, and the pumped storage unit generates mutually exclusive constraint, and the expression of the constraint is as follows:
6) the corrected value of the rolling schedule is associated with the original planned value, the output value of each unit after correction and the output deviation of the day-ahead plan need to be controlled within a certain range, the coordination between the day-ahead schedule and the day-ahead schedule is ensured, and the expression of the rolling schedule deviation constraint is as follows:
In the fourth step, considering that the power generation cost of the conventional thermal power generating unit has an expression in a quadratic function form, the power spot market allows the power generating unit to submit multiple sections of quotations, namely an output-price step curve (piecewise function), and each section of quotation is monotonically non-decreasing; the established model is mainly solved by using a 0-1 integer linear programming method, the optimization result obtained by solving the problem by adopting linear programming is considered to be ideal, the piecewise function of the electric quantity price needs to be linearized when the planned operation curve of the unit is cleared, and the specific linearization process of the electric quantity price is as follows by taking one unit as an example:
wherein the content of the first and second substances,
a starting point and an end point corresponding to the ith section of the unit, CiThe electricity price corresponding to the i-th section of the unit output interval is sequentially increased according to the capacity, C is electricity price information of the unit output corresponding to linearization at a certain time, n is considered to be 3 sections, namely, the output range of the unit is divided into 3 sections for declaration, and a 0-1 integer variable K is introducediThe electricity price is linearized.
Preferably, the solution of the intraday rolling optimization model of the pumped storage group is a 0-1 mixed integer linear programming method.
The day-by-day optimized scheduling method for researching the pumped storage unit under the spot market environment has the following beneficial effects:
1) the method has the advantages that the characteristic that the output prediction precision of the renewable energy is improved along with the shortening of the prediction time is considered, the clear result of the daily electric energy trading is used as the calculation basis, a rolling plan revision model is provided, the following problem of the power generation plan is better processed by designing the rolling deviation value constraint, and the new energy is better absorbed;
2) the method takes the background that cost recovery is difficult due to the current operation mode of the pumped storage power station into consideration, introduces the pumped storage power station into the spot market, takes the pumped storage operation benefit into consideration in the provided intraday rolling optimization model with the pumped storage unit, and ensures the maximum consumption of new energy in the process of dispatching the pumped storage according to needs;
3) the invention is organized and expanded under the background of spot market, relates to the process of reporting the electricity price information by related market main bodies, and better solves the problem of sectional quotation of power generation and utilization parties after 0-1 variable is introduced.
Drawings
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
FIG. 1 is a flow chart of intraday rolling optimization scheduling with pumped-storage units in a spot market environment;
FIG. 2 is a flow chart of a day market exchange organization;
FIG. 3 is a time chart of intra-day scrolling;
FIG. 4 is a schematic diagram showing new energy consumption;
FIG. 5 is a schematic view of a rolling revised unit operating curve;
fig. 6 is a schematic diagram of the operating state and the output condition of each pumped storage unit.
Detailed Description
The technical scheme of the invention is explained in detail in the following by combining the drawings and the embodiment.
The intraday rolling optimization scheduling method for the pumped storage unit under the spot market environment is characterized by comprising the following steps of:
step one, designing a spot-shipment transaction process in the day;
1) the transaction preparation phase mainly works as follows: after the market is cleared and closed by trading in the day, all direct-adjustment generator sets and stations need to provide operation parameters for market operation mechanisms in the day market, and each market main body reports the up-adjustment and down-adjustment capacity and price information of the operation day according to the requirements of daily spot market trading clearing result, daily power grid load fluctuation, temporary safety adjustment and the like. The market operating mechanism synthesizes related information and releases the operation parameters and boundary condition information of the spot market in the day to a related market main body 4h in advance;
2) the market is gone out clear stage and is mainly worked: taking 4h as a daily trading period, taking every 15min as a trading clearing period, wherein each trading period comprises 16 trading clearing periods, the daily market is opened for 6 times each day, taking the former two trading periods as an example, fig. 3 is a specific rolling sequence diagram, T is a trading execution time, based on the optimization clearing result of the market in the day ahead, the ultra-short-term load prediction and the new energy output prediction information updated in real time, comprehensively considering the related network security constraints, performing the optimization clearing in the day, before (T-140) min, a unit operation plan curve (16 points) of a transaction period in the day is cleared, before (T-110) min, the market operating mechanism carries out alternating current power flow safety check on the unit output curve in the time interval, if the constraint is not met, adding corresponding constraint conditions into the model, and repeating the process until the constraint conditions are met to obtain a time-sharing power generation output curve of the trade time period in the day;
3) the main work of the information issuing and executing stage is as follows: (T-80) before min, the market technical support system issues within-day trade clearing results to relevant market subjects. After being audited, each market subject returns confirmation information, and the market subject with disputed clearing result can provide explanation application to the market operating organization;
acquiring basic data of the power system;
1) day-ahead 96-point operation plan of thermal power generating unit
Operating state I of each thermal power generating uniti,t；
2) New energy field (station) information: number of new energy fields (stations) NMNew energy field (station) number i, new energy ultra-short term power prediction information Qi,tThe new energy yield is higher or lower than the expected percentage fu％、fd％；
3) Load ultra-short term prediction value L of certain areain,tPlanned value L for power supplyoff,tThe load is higher or lower than the expected percentage lu％、ld％；
4) Information of a fire generator set in the power system: total number N of thermal power generating unitsGNumber i of thermal power generating units and maximum active power output P of each thermal power generating uniti maxMinimum active power output Pi minAnd rated power Pi EUpward slope velocity Δ Pi UDownward climbing rate delta Pi D；
5) Pumped storage power station information: number of pumped storage groups NHNumber i of pumped storage group, maximum power generation power of pumped storage group
Water pumping power
Maximum reservoir capacity E of upper reservoir of pumped storage power stationmaxMinimum storage capacity EminPumping efficiency etalAnd electric power generation efficiency etag；
6) The price information of the electric quantity declared by the market main body is as follows: thermal power generating unit Ci,t(Pi,t) And a new energy station Ci,t(Fi,t) Pumped storage unit Ci,t(Pg,i,t)；
Establishing an intraday rolling optimization model containing the pumped storage unit, wherein the model consists of an objective function and constraint conditions;
step four, carrying out linear processing on the electric quantity price piecewise function declared by each market subject;
and step five, calling a mature linear programming software package to solve through a linear programming solving model which is a 0-1 mixed integer linear programming model, such as GLPK, so as to obtain a unit plan operation curve in the transaction period.
In the third step, in the day rolling optimization model objective function containing the pumped storage unit in the market environment, the maximum overall benefit of the system is considered, a part of benefits of the pumped storage power station are guaranteed, meanwhile, the unit operation result information obtained by planning in the day before is taken as the calculation basis, the rolling plan correction value deviation constraint is added in the constraint condition, the corrected unit output plan can be guaranteed to better follow the day before plan under the condition that new energy is maximally absorbed by the system, partial adjustment cost is reduced, and finally, the day market price information is also subjected to linearization treatment, so that the problem of market main body section quotation is well solved;
in conclusion, the objective function comprehensively considers that the overall efficiency of the system operation is maximum, and the objective function is as follows:
wherein, Pi,tA force value is planned for the thermal power generating unit i in the day of the time period t,
and the power is added or subtracted for the thermal power generating unit i in the time period t. Fi,tForce values are planned for the new energy station i within the day of the time period t,
for increasing and decreasing the power of the new energy station i in the time period t,
increasing and decreasing force P of the pumped storage unit i in the power generation state in a time period tg,i,tThe method comprises the steps of designing a force value for a pumped storage unit i in a power generation state within a time period t, and utilizing the difference value between a day-ahead plan and a day-in plan of the unit to express the increased and decreased force of the unit at a certain moment, Ci,t(Pi,t)、Ci,t(Fi,t)、Ci,t(Pg,i,t) Is a multi-section linear function related to the output intervals and the corresponding energy prices reported by the thermal power generating unit i, the new energy station i and the pumped storage unit i,
the state variable for generating the pumped storage unit, wherein 1 is a power generation state, 0 is a shutdown state, and N isGNumber of thermal power units of system, NMNumber of new energy stations for the system, NHFor number of pumped storage groups, T1Is a clearing period of 16 points in a trading cycle in one day.
In the third step, the constraint conditions of the built model include: the system comprises a system power balance constraint, a unit output constraint, a thermal power unit climbing constraint, a system rotation standby constraint, a pumped storage unit power generation constraint, a reservoir capacity balance constraint and a rolling planned value deviation constraint.
1) The expression of the above system power balance constraint is:
in the formula Pl,i,tFor pumped storage machinesThe water pumping power of the group i in the water pumping state,
state variables for pumping water of the pumped storage unit; 1 is a pumping state, 0 is a shutdown state, Lin,t、Loff,tRespectively is a certain regional load ultra-short term predicted value and an outsourcing power plan value of the transaction time interval t.
2) The expression of the unit output constraint is as follows:
Ii,t*Pi min≤Pi,t≤Ii,t*Pi max
Fi,t≤Qi,t
in the formula Pi max、Pi minThe upper and lower output limits Q of the thermal power generating unit ii,tPredicting the maximum output of the new energy station i in the time period t; i isi,tThe method comprises the following steps of (1) obtaining a state variable of a thermal power generating unit i in operation at a time t; 0 is a shutdown state, and 1 is an operation state; determined by a day-ahead plan.
3) The climbing constraint expression of the thermal power generating unit is as follows:
Pi,t-Pi,t-1≤△Pi U
Pi,t-1-Pi,t≤△Pi D
△Pi U、△Pi Dand the maximum up-down climbing speed of the thermal power generating unit i is obtained.
4) The expression of the above system rotation reserve constraint is:
in the formula Iu％、ld% load higher or lower than expected, fu％、fd% ofThe new energy yield is higher or lower than the expected percentage.
5) In the rolling optimization scheduling stage in the daytime, the pumped storage unit is mainly used for balancing the new energy output prediction error, so that the output, the storage capacity and the like of a pumped storage power station need to be constrained:
5.1) the pumping storage unit pumps water for full power, only considering the output constraint of the generating state unit, wherein the expression of the constraint is as follows:
in the formula
The maximum output is the maximum output of the pumped storage unit i during power generation;
5.2) the expression of reservoir capacity constraint is:
Emin≤Et≤Emax
in the formula EtMeasured by the electric quantity for the capacity of the reservoir at time t of the pumped storage power station, Emax、EminThe maximum and minimum storage capacities of the upper reservoir of the pumped storage power station are set;
5.3) the expression of the reservoir capacity balance constraint is:
in the formula etal、ηgThe water pumping and power generation efficiency of the water pumping and energy storage unit is improved;
5.4) the pumped storage unit can not generate power and pump water simultaneously, and the pumped storage unit generates mutually exclusive constraint, and the expression of the constraint is as follows:
6) the corrected value of the rolling schedule is associated with the original planned value, the output value of each unit after correction and the output deviation of the day-ahead plan need to be controlled within a certain range, the coordination between the day-ahead schedule and the day-ahead schedule is ensured, and the expression of the rolling schedule deviation constraint is as follows:
in the formula
And (5) a force value is planned for the unit i day ahead. Pi EAnd xi is a constraint multiplier for the rated power of the unit i, and the maximum allowable correction deviation of the scheduling in the day can be changed by adjusting the size of the constraint multiplier.
In the fourth step, the electric quantity price piecewise function linearization process is as follows:
in the formula (I), the compound is shown in the specification,
starting point and end point corresponding to the ith section of output interval declared for the unit, CiSequentially increasing the electricity price corresponding to the i-th section of the unit according to the capacity, C is electricity price information of the unit after the output is correspondingly linearized at a certain time, considering that n is 3 sections, and introducing a 0-1 integer variable KiThe electricity price is linearized.
Preferably, the solution of the intraday rolling optimization model of the pumped storage group is a 0-1 mixed integer linear programming method.
Taking the data of a certain provincial power grid as a calculation basis, wherein the number of nodes of the power flow bus of the power grid is 1925, 851 lines are provided, 934 transformers are provided, and 561 generators (including equivalent generators of a wind-light power plant) are provided; the equivalent wind power plants are 224, the photovoltaic power stations are 95, the capacity of a direct-regulation wind power generator is 18446.34MW, and the installed capacity of a direct-regulation photovoltaic power generator is 7240.1 MW. The region is provided with a pumping storage power station which is provided with 4 300MW pumping storage units, and the total installed capacity is 1200 MW; the maximum energy storage is 7.4h for full power, and 9.15h for full power water pumping. The rolling period is set to be 8: 15-12: 00, namely time 33-48, various data needed by an optimization algorithm are automatically obtained from a D5000 platform, then the model and the optimization method are verified, the established optimization model is a 0-1 mixed integer linear programming model, 57466 variables are provided in total, 9200 integer variables and 58193 constraint conditions are adopted, the linear programming software package GLPK of a free software project GNU is adopted for solving, the problem scale is large and mostly is 0-1 variable, a Fischetti-Monaci proximity search heuristic algorithm is adopted, the algorithm can rapidly improve the feasible solution of the mixed integer programming problem, the problem that the optimal solution can be obtained for a long time can rapidly obtain the suboptimal solution, and the solving rate is greatly improved.
The new energy consumption condition, the plan operation curve after the unit correction and the operation state result of the pumped storage unit are shown in fig. 4, fig. 5 and fig. 6.
From fig. 4, it can be seen that the new energy ultra-short-term predicted output and the actual output in all time periods in the rolling period are consistent, and there is no wind and light abandoning phenomenon in one period, which shows that the established model can be better for the renewable energy consumption in most of the time.
The operation curves of the wind power plant, the photovoltaic power station, the pumped storage power station and the thermal power generating unit planned operation curve after rolling correction are shown in fig. 5, and it can be seen that at 9: 00-12: 00, the load is reduced, the total output of new energy is basically kept stable, in order to absorb more new energy, the pumped storage power station unit is basically operated in a pumped state, the output of the thermal power generating unit is stable, the peak regulation pressure of the power generating unit is reduced, and optimal configuration of various energy sources is achieved.
The operation states and output conditions of 4 machine groups of the pumped storage power station are shown in figure 6, the change of the water storage capacity of an upper reservoir is measured by electric quantity and is determined by the operation states of the 4 machine groups, the figure shows that the pumped storage power station is in a power generation state at the ratio of 8:15-8:45, the pumped storage power station arranges the corresponding machine groups to pump water to operate due to the slow increase of the output of new energy at other time intervals, and the pumped storage machine groups are scheduled as required to ensure the complete consumption of the new energy along with the change of the output conditions of the new energy.
Claims (7)
1. The intraday rolling optimization scheduling method for the pumped storage unit under the spot market environment is characterized by comprising the following steps of:
step one, designing a spot-shipment transaction process in the day;
acquiring basic data of the power system;
step three, establishing an intraday rolling optimization model containing a pumped storage unit;
step four, carrying out linear processing on the electric quantity price piecewise function declared by each market subject;
and step five, solving the rolling optimization model in the day to obtain a unit plan operation curve in the trading period.
2. The intraday rolling optimization scheduling method including the pumped-storage unit in the spot market environment according to claim 1, wherein in the first step, the intraday spot market transaction process includes three stages of transaction preparation, market clearing, transaction information release and execution.
3. The method for rolling and optimizing scheduling in the daytime including pumped storage units in the spot market environment according to claim 1, wherein in the second step, the basic data includes a schedule of thermal power units being started and cleared by a day-ahead unit 96 with 15min as a point, operation state information, thermal power unit information, new energy station information, pumped storage power station information, regional load prediction information, and electric quantity price information declared by market entities in the daily market.
4. The method for optimizing scheduling in the daytime for studying pumped-storage group under spot market environment according to claim 1, wherein in step three, the objective function of the model for optimizing rolling in the daytime for studying pumped-storage group is as follows:
wherein, Pi,tA force value is planned for the thermal power generating unit i in the day of the time period t,
for increasing or decreasing the power of the thermal power generating unit i in the time period t, Fi,tA force value is output for the new energy station i within the day of the time period t,
for increasing and decreasing the power of the new energy station i in the time period t,
increasing and decreasing force P of the pumped storage unit i in the power generation state in a time period tg,i,tA force value C is planned for the clearing of the pumped storage unit i in the power generation state within the time period ti,t(Pi,t)、Ci,t(Fi,t)、Ci,t(Pg,i,t) Is a multi-section linear function related to the output intervals and the corresponding energy prices reported by the thermal power generating unit i, the new energy station i and the pumped storage unit i,
the state variable for generating the pumped storage unit, wherein 1 is a power generation state, 0 is a shutdown state, and N isGNumber of thermal power units of system, NMNumber of new energy stations for the system, NHFor number of pumped storage groups, T1Is a clearing period of 16 points in a trading cycle in one day.
5. The method for optimizing scheduling in the daytime for studying pumped-storage units in spot market environment according to claim 1, wherein in step three, the constraints of the established model include: the system comprises a system power balance constraint, a unit output constraint, a thermal power unit climbing constraint, a system rotation standby constraint, a pumped storage unit power generation constraint, a reservoir capacity balance constraint and a rolling planned value deviation constraint.
6. The method for optimizing scheduling in the daytime for studying pumped storage units in spot market environment according to claim 1, wherein in the fourth step, the quantity price piecewise function linearization process is as follows:
wherein the content of the first and second substances,
starting point and end point corresponding to the ith section of output interval declared for the unit, CiThe electricity price corresponding to the i-th section of the output interval is sequentially increased according to the capacity, C is linearized electricity price information, n is considered to be 3 sections, and a 0-1 integer variable K is introducediThe electricity price is linearized.
7. The method for optimizing scheduling in the daytime for studying the pumped storage group in the spot market environment according to claim 1, wherein in the fifth step, the intraday rolling optimization model of the pumped storage group is solved, and a linear programming method with an integer of 0 to 1 is adopted.
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