A method for determining the real-time reserve rate of renewable energy power sources in medium and long time scales

Abstract

The present invention belongs to the technical field of power system planning and operation scheduling, and discloses a method for determining the real-time reserve rate of a new energy power source in a medium and long time scale. The method comprises three steps: obtaining the uncertain time series output of new energy, establishing a multi-source power production simulation model including new energy power sources, and solving the multi-source power production simulation model to obtain the real-time reserve rate of the reliable predicted output of new energy in each time period. The output of part of the new energy is incorporated into the system reserve to alleviate the problem of insufficient reserve caused by large-scale new energy access to the power system. In order to eliminate the influence of new energy prediction error and uncertainty on the inclusion of reserve, the concept of reliable prediction accuracy rate of new energy power generation is introduced, the predicted time series data is multiplied by the reliable prediction accuracy rate to obtain the reliable output data of new energy, the reliable output of new energy is incorporated into the system reserve, and the capacity of new energy included in the reserve is adjusted in real time according to the system reserve demand by the real-time reserve rate method.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system planning and operation scheduling, and specifically relates to a method for determining the real-time standby rate of a new energy power source in a medium to long time scale. Background Art

[0002] With the increase in the penetration rate of new energy sources, the system flexibility resources are seriously insufficient. At the same time, factors such as cross-regional UHV DC blocking failures and increasingly high power supply reliability requirements have increased the backup demand on various time scales of the power system. At present, measures such as hydropower, pumped storage, fuel gas turbines and other peak-shaving units, transformation of thermal power units or demand-side response are usually adopted to improve the flexibility of system operation.

[0003] As the penetration rate of renewable energy power generation continues to increase, the traditional rotating reserve method will not be able to meet the needs of the system. According to the "GB38755-2019 Guidelines for Power System Safety and Stability", the renewable energy power generation side is required to improve its regulation capability and have primary frequency regulation capability. Therefore, with the improvement of the prediction accuracy of renewable energy power generation output and the accumulation of operating experience, it is necessary and possible to include some renewable energy power generation in the system reserve. Based on statistical characteristics and taking into account renewable energy consumption and grid safety, some scholars have included renewable energy in multiple regions at a fixed ratio on the basis of statistically analyzing the accuracy of renewable energy reliable predictions, and given the impact of load loss risk, renewable energy prediction accuracy, and load prediction level factors on the reserve ratio. Including a certain proportion of renewable energy output in the system reserve can improve the safety and reliability of system operation and alleviate the pressure of insufficient system reserve. Affected by the randomness and volatility of renewable energy output, using a fixed proportion of renewable energy as reserve cannot reduce the operating cost very well. Including the reliable predicted output of renewable energy in the system reserve at a fixed ratio, the reserve capacity is determined by the real-time output of renewable energy. When the system reserve demand changes, the reserve capacity of traditional units can only be adjusted, which has problems such as poor flexibility and economy. Existing methods incorporate renewable energy into reserves in short-term date scheduling models, but fail to analyze the impact of incorporating renewable energy into reserves on the medium- and long-term operation of large-scale renewable energy power systems from the perspective of medium- and long-term scheduling and planning. Summary of the invention

[0004] The purpose of the present invention is to provide a method for determining the real-time reserve rate of renewable energy power sources in medium and long term time scales, incorporate the reliable output of renewable energy power sources into the production reserve of the power system, adjust the proportion of renewable energy included in the reserve in each time period in real time according to the real-time output of renewable energy and the peak load demand of the system, and improve the operation flexibility and economy of the system in medium and long term time scales.

[0005] The technical solution adopted by the present invention is a method for determining the real-time standby rate of new energy power sources in the medium and long term, comprising the following steps:

[0006] S1. Obtain the uncertain timing output of new energy;

[0007] S2. Establish a multi-source power production simulation model including new energy power sources;

[0008] S3. Solve the multi-source power production simulation model of step S2 to obtain the real-time reserve rate of the reliable predicted output of new energy in each time period.

[0009] Furthermore, the step S1 specifically includes the following steps:

[0010] S101. Sampling historical data to establish a randomness and uncertainty model for new energy;

[0011] S102, using the k-medoids clustering method to replace the same or similar scenes with representative scenes to eliminate data redundancy;

[0012] S103. Consider the influence of errors and uncertainties to obtain the final predicted time series output.

[0013] Furthermore, the step S2 specifically includes: establishing a production simulation model with the goal of optimizing the production simulation cost, taking into account the output characteristics and output constraints of various units in the system, power balance constraints, and the reserve constraints of incorporating new energy into system reserve at a real-time reserve rate.

[0014] Furthermore, the production simulation cost includes the operating cost, startup and shutdown cost, pollution control cost, and new energy power abandonment penalty cost and load shedding penalty cost of the generator set, and specifically includes the following steps:

[0015] A. Use the following formula to calculate the overall system operating cost f 1 :

[0016]

[0017] In the formula, f t is the operating cost function of various units during period t; RC , P t curW Respectively represent the penalty coefficient for abandoned power of new energy and the amount of abandoned power of new energy; λ LC , P t curL Represent the load shedding penalty coefficient and load shedding power respectively; λ Ci,t , S i,t They represent the pollution control cost and pollution discharge corresponding to the power generation of the i-th generator in period t respectively;

[0018] B. Use the following formula to calculate the operating cost function f of each type of unit during period t t :

[0019]

[0020] In the formula, f j (P i,t ) is the function of the unit operation and maintenance cost and output size; Binary state variable for the unit on / off; represents the startup and shutdown cost of the i-th unit;

[0021] C. Use the following formula to calculate the amount of abandoned new energy P t curW :

[0022]

[0023] In the formula, represents the maximum power output of the wind farm during period t; P t wind Indicates the real-time output of wind farm dispatch during period t; represents the maximum power generation output of the photovoltaic power plant during period t; P t pv Indicates the real-time output of the photovoltaic power field during period t;

[0024] D. Use the following formula to calculate the load shedding power P t curL :

[0025]

[0026] In the formula, Indicates the real-time load of the system; P load Indicates the load involved in scheduling balance.

[0027] Furthermore, the output constraints of various units in the system are expressed as:

[0028] a. Output constraints of wind power and photovoltaic units:

[0029]

[0030] In the formula, Represents the maximum output of the wind turbine during period t; Represents the maximum output of photovoltaic power generation during period t;

[0031] b. Output constraints of CSP units:

[0032] The output constraints of the CSP unit include the dynamic balance constraint of the heat of the collector field, the dynamic balance constraint of the heat of the heat storage tank, the upper and lower limit constraints of the generator output, and the climbing constraint:

[0033] Dynamic balance constraints of heat in the collector field:

[0034] In the formula, They are the heat used by the CSP station for power generation during period t, the total solar heat absorbed by the collector field, the heat stored in the heat tank by the CSP station, and the heat abandoned by the CSP station; The thermal efficiency of the collector field in absorbing heat and transferring it to power generation;

[0035] Dynamic balance constraints of heat storage tank:

[0036] In the formula, They are the heat stored in the heat tank, the heat transferred from the collector field to the heat storage tank, and the heat transferred from the heat storage tank to the power generation side during period t. The heat storage efficiency of the heat storage tank;

[0037] Thermoelectric conversion efficiency constraints:

[0038] In the formula, The power generation efficiency of the CSP station; The power output of the CSP station at time t;

[0039] Upper and lower limits of power generation output of CSP stations:

[0040] In the formula, Provide the minimum technical contribution for CSP power stations; Provide the greatest technical contribution to CSP plants;

[0041] Thermal storage tank capacity constraints:

[0042] In the formula, Represents the minimum and maximum heat storage capacity of the heat storage tank;

[0043] Climbing constraints of generators in CSP power plants:

[0044] In the formula, R is the binary state variable of the unit startup; U / R D are the maximum up and down climbing capabilities of the generator respectively;

[0045] c. Output constraints of thermal power units:

[0046] The output constraints of thermal power units include maximum and minimum technical output constraints and ramp constraints;

[0047] Output upper and lower limits of thermal power units: P i,tmin ≤P i,t ≤P i,tmax

[0048] Where P i,tmin / Pi,tmax The minimum / maximum technical output of thermal power units;

[0049] Thermal power unit climbing constraints:

[0050] Where P i,t , P i,t+1 represents the output of the i-th thermal power unit during period t and period t+1; ΔP i,up / ΔP i,down is the ramp-up / downward rate of the coal-fired unit;

[0051] d. Hydropower unit output constraints:

[0052] Output equation constraints of hydropower units:

[0053] In the formula, Q h (t) is the power generation flow of hydropower unit i in period t; H(t) is the power generation head at time t; η G,i is the turbine efficiency of hydropower unit i in period t; η T,i is the generator efficiency of hydropower unit i in period t;

[0054] Among them, the power generation flow constraint is: Q h (t) = min(Q h,out (t),Q h,out,max ), Q h,out (t) is the outflow capacity of the hydropower unit at time t; Q h,out,max is the maximum outbound flow rate;

[0055] Outbound capacity equality constraint: Q h,out (t) = Q h (t)+Q h,c (t), Q h,c (t) is the water flow limit;

[0056] Outbound flow upper and lower limit constraints: 0<Q h,out (t)<Q h,out,max , Q h,out,max is the maximum outbound flow rate;

[0057] Storage capacity equality constraint: C h (t) = C h (t-1)+Q h,in (t)ΔT-Q h,out (t)ΔT,C h (t) is the storage capacity of the reservoir in period t; Q h,in (t) is the inflow flow of the hydropower unit in period t;

[0058] Maximum and minimum storage capacity constraints: C h,min(t)≤C h (t)≤C h,max (t), C h,max / C h,min is the maximum / minimum storage capacity limit of the reservoir in period t;

[0059] Climbing constraints of hydropower units:

[0060] In the formula, is the uphill / downhill rate of the hydropower unit, is the output of hydropower unit i at time t,

[0061] e. Nuclear power unit constraints:

[0062] Nuclear power unit output upper and lower limit constraints:

[0063] In the formula, Represents the lower and upper limits of the power generation of the i-th nuclear power unit; represents the output of the i-th nuclear power unit during period t;

[0064] Nuclear power unit climbing constraints:

[0065] In the formula, represents the maximum uphill and downhill capability of the i-th nuclear power unit;

[0066] f. Constraints of electrochemical energy storage units:

[0067] Energy storage capacity upper and lower limits: 0≤S OCi,t ≤S OCi,max

[0068] In the formula, S OCi,max , S OCi,t are the maximum capacity of the energy storage battery and the battery charge at time t respectively;

[0069] Energy storage capacity balance constraints:

[0070] In the formula, Represents the charging / discharging state of the energy storage battery during period t; P bat,i+ (t) represents the power of the energy storage battery during the discharge process of time period t; P bat,i- (t) represents the power of the energy storage battery charging process during period t; η c / η d Energy storage battery charging efficiency and discharging efficiency;

[0071] Energy storage charging and discharging power constraints:

[0072] Where: P bat,i+min / Pbat,i+max Represents the minimum and maximum power of the energy storage battery during discharge; P bat,i-min / P bat,i-max Represents the minimum and maximum power of the energy storage battery charging process;

[0073] g. Pumped storage unit constraints:

[0074] Pumped storage unit climbing constraints:

[0075] In the formula, is the pumping and generating power of the i-th unit of the pumped storage power station during period t; Represents the maximum downhill and uphill capacity of a pumped storage power station during pumping;

[0076] Power constraints during pumping and power generation:

[0077] In the formula, Represents the minimum and maximum power of the pumping process of the pumped storage power station; Represents the minimum and maximum power of the power generation process of the pumped storage power station;

[0078] Storage capacity constraints of pumped storage power stations:

[0079]

[0080] In the formula, Q h,in (t) / Q h,out (t) represents the inflow and outflow of the warehouse during the period t; η c,cx / η d,cx Represents the pumping and power generation efficiency of the pumped storage power station; S h,ma x / S h,min , S h (t) represents the maximum and minimum storage capacity of the pumped storage power station and the pumped storage capacity during period t, respectively; They represent the inbound and outbound traffic status during period t respectively.

[0081] Further, the power balance constraint is expressed as follows:

[0082]

[0083] In the formula, P t csp , P t pv , P t wind , P bat,i+ (t), P t curWThey represent the coal-fired power generation, oil-fired power generation, gas-fired power generation, hydropower generation, nuclear power generation, solar thermal power generation, pumped storage power generation, photovoltaic power generation, wind power generation, energy storage charging and discharging power, and new energy curtailment power during period t respectively; P t load , P bat,i- (t) P t curL They represent the load power, battery charging power, pumped storage power and load shedding power in period t respectively.

[0084] Further, the backup constraint is expressed as follows:

[0085]

[0086] Where P i,max (i, t) represents the maximum allowable output of unit i during period t; P(i, t) represents the real-time power generation output of unit i during period t; represents the operating status of unit i during period t; β t is the real-time reserve rate of renewable energy power generation, η is the reliable prediction accuracy of renewable energy power generation; P re,t Represents the spinning reserve capacity of the system during period t.

[0087] Furthermore, it also includes a logical variable constraint, which is expressed as follows:

[0088]

[0089] In the formula, Represents the operating status of unit i during period t. When unit i is in the operating state during period t It is the minimum duration of the unit state, that is, the unit must run for a certain period of time before the state transition can be performed.

[0090] Furthermore, step S3 specifically includes: solving the multi-source power production simulation model obtained in step S2, obtaining the credible predicted output of new energy in each time period under the most economical condition of power system operation, incorporating the real-time reserve rate, incorporating the new energy in each time period into the power system reserve according to the obtained real-time reserve rate, and obtaining the output of each unit in each time period under the optimal target.

[0091] Furthermore, the method for solving the multi-source power production simulation model is to solve it by calling the CPLEX solver through MATLAB.

[0092] The beneficial effects of the present invention are:

[0093] By incorporating part of the output of renewable energy into the system reserve, the problem of insufficient reserve caused by large-scale renewable energy access to the power system can be alleviated. In order to eliminate the impact of renewable energy prediction errors and uncertainties on the inclusion of renewable energy into the reserve, the concept of reliable prediction accuracy of renewable energy power generation is introduced. The predicted time series data is multiplied by the reliable prediction accuracy to obtain the reliable output data of renewable energy. The reliable output of renewable energy is the power that renewable energy can fully guarantee to generate during the simulation period. The reliable output of renewable energy is included in the system reserve, and the capacity of renewable energy included in the reserve is adjusted in real time according to the system reserve demand by the real-time reserve rate method. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 It is a schematic diagram of the process of the present invention.

[0095] Figure 2 This is a flow chart of the uncertainty modeling method for renewable energy power sources in the medium and long term.

[0096] Figure 3 This is a calculation flow chart of the present invention.

[0097] Figure 4 This is the real-time reserve rate diagram for 720 hours of new energy generation included in system reserve when the new energy penetration rate is 30%. DETAILED DESCRIPTION

[0098] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0099] See also Figure 1 The implementation process of the present invention is divided into the following three steps:

[0100] S1. Use the time series simulation method to obtain the uncertain time series output of new energy. First, sample the historical data to establish the randomness and uncertainty model of new energy. Then use the k-medoids clustering method to replace the same or similar scenes with representative scenes to eliminate data redundancy. Finally, consider the influence of error and uncertainty to obtain the final predicted time series output.

[0101] S2. With the goal of optimizing the overall operating cost of the system, a multi-source power production simulation model is established by considering the output characteristics and operating constraints of wind power, photovoltaic power generation, solar thermal power generation, hydropower, thermal power, nuclear power, oil power generation, natural gas power generation, energy storage, pumped storage and other power generation sources. The reliable output of new energy power sources is included in the production reserve of the power system. The reliable predicted output of new energy power sources in each time period is included in the reserve, and a method for determining the real-time reserve rate is given.

[0102] S3. Solve the model to obtain the reliable predicted output of new energy in each period under the most economical condition of power system operation and include it in the real-time reserve rate. Incorporate the new energy in each period into the power system reserve according to the obtained real-time reserve rate. Obtain the output of each unit in each period under the optimal goal.

[0103] In a feasible embodiment, specifically, the detailed process of implementing step S1 is as follows, see Figure 2 :

[0104] (1) Using the time series simulation method to obtain the uncertain time series output of new energy;

[0105] (2) First, input historical data and calculate the distribution parameters that the historical data obeys in each month;

[0106] (3) Secondly, Latin cube sampling is performed based on the calculated distribution parameters to obtain random photovoltaic, wind power, and load scenarios;

[0107] (4) Secondly, the k-medoids clustering method is used to replace the same or similar scenes with representative scenes to eliminate data redundancy;

[0108] (5) The next step is to calculate the state transition probability matrix under each scenario, and sort the scenarios according to the state transition probability matrix to obtain a time series with a length of one month;

[0109] (6) Finally, repeat the above steps to obtain the time series output required for the production simulation.

[0110] In a feasible embodiment, specifically, the implementation process of step S2 is as follows:

[0111] With the goal of optimizing the production simulation cost, a production simulation model is established by considering the output characteristics and constraints of thermal power, oil, gas, hydropower, nuclear power, solar thermal, energy storage, pumped storage and other units, as well as the power balance constraints and the inclusion of new energy into the system reserve at the real-time reserve rate.

[0112] Specifically, the optimization goal is to minimize the production simulation cost. The production cost includes the operating cost of the generator set, the cost of starting and stopping the machine, the cost of sewage treatment, the penalty cost of abandoning new energy power, and the penalty cost of load shedding.

[0113] Overall system operating cost:

[0114]

[0115] In the formula, f t coal 、f t oil 、f t gas 、ft hydro 、f t nuclear 、f t csp 、f t bat 、f t cx Represent the power generation cost functions of coal-fired, oil-fired, gas-fired, hydropower, nuclear power, solar thermal, energy storage, pumped storage and other units respectively; λ RC The penalty coefficient for abandonment of renewable energy is set at 50 USD / MW·h. t curW Represents the amount of abandoned renewable energy, obtained by calculation; λ LC The load shedding penalty coefficient is set at $500 / MW·h, P t curL is the load shedding power, obtained by calculation; Ci,t is the pollution control cost corresponding to the power generation of the i-th generator in period t, where the carbon dioxide control cost is 0.0153 US dollars / pound, the sulfur dioxide control cost is 25.1 US dollars / pound, and S i,t They respectively represent the pollution discharge corresponding to the power generation of the i-th generator in period t.

[0116] Abandoned electricity from new energy sources:

[0117]

[0118] In the formula, represents the maximum power output of the wind farm during period t; P t wind Indicates the real-time output of wind farm dispatch during period t; represents the maximum power generation output of the photovoltaic power plant during period t; P t pv Indicates the real-time output of the photovoltaic power field during period t.

[0119] Load shedding power:

[0120]

[0121] In the formula, Indicates the real-time load of the system; P load Indicates the load involved in scheduling balance.

[0122] Specifically, the constraint establishment process is as follows:

[0123] Power balance constraints:

[0124]

[0125] In the formula, Pt csp , P t pv , P t wind , P bat,i+ (t), P t curW They represent the coal-fired power generation, oil-fired power generation, gas-fired power generation, hydropower generation, nuclear power generation, solar thermal power generation, pumped storage power generation, photovoltaic power generation, wind power generation, energy storage charging and discharging power, and new energy curtailment power during period t. t load , P bat,i- (t) P t curL They represent the load power, battery charging power, pumped storage power and load shedding power in period t respectively.

[0126] By incorporating part of the output of renewable energy into the system reserve, the problem of insufficient reserve caused by large-scale renewable energy access to the power system can be alleviated. In order to eliminate the impact of renewable energy prediction errors and uncertainties on the inclusion of renewable energy into the reserve, the concept of reliable prediction accuracy of renewable energy power generation is introduced. The predicted time series data is multiplied by the reliable prediction accuracy to obtain the reliable output data of renewable energy. The reliable output of renewable energy is the power that renewable energy can fully guarantee to generate during the simulation period. The reliable output of renewable energy is included in the system reserve, and the capacity of renewable energy included in the reserve is adjusted in real time according to the system reserve demand by the real-time reserve rate method.

[0127] Alternative constraints:

[0128]

[0129] Where P i,max (i, t) represents the maximum allowable output of unit i during period t; P(i, t) represents the real-time power generation output of unit i during period t; Indicates the operating status of unit i during period t. t is the real-time reserve rate of renewable energy power generation, η is the reliable prediction accuracy of renewable energy power generation; P re,t Represents the spinning reserve capacity of the system during period t.

[0130] Specifically, the output constraints of various units are expressed as follows:

[0131] a. Output constraints of wind power and photovoltaic generators:

[0132] The sum of the power generation output of wind power and photovoltaic power generation in period t and the included reserve power is between the maximum output and 0 in period t.

[0133]

[0134] In the formula, Represents the maximum output of wind power during period t; Represents the maximum output of photovoltaic power generation during period t.

[0135] b. Output constraints of CSP units:

[0136] The constraints of the CSP power station model include the dynamic balance of heat in the collector field, the dynamic balance of heat in the heat storage tank, the upper and lower limits of the generator output, and the ramp limit.

[0137] The cost of power generation from a solar thermal power station:

[0138]

[0139] In the formula, f t csp is the total operating cost of the CSP unit during period t. is the function of operation and maintenance cost and output size of the CSP unit; Binary state variable for the unit on / off; represents the startup and shutdown cost of the i-th CSP generator, which is 10,000 USD per time;

[0140] Thermal balance constraints of the collector field:

[0141]

[0142] In the formula, They are the heat used by the CSP station for power generation during period t, the total solar heat absorbed by the collector field, the heat stored in the heat tank by the CSP station, and the heat abandoned by the CSP station; The thermal efficiency of the collector field in absorbing heat and transferring it to power generation is 96%.

[0143] Hot tank heat balance constraints:

[0144]

[0145] In the formula, The heat stored in the heat tank during period t, the heat transferred from the collector field to the heat storage tank, and the heat transferred from the heat storage tank to the power generation side; is the heat storage efficiency of the heat storage tank, which is 96%;

[0146] Thermoelectric conversion efficiency constraints:

[0147]

[0148] In the formula, is the power generation efficiency of the CSP plant, which is 48%; The power output of the CSP station at time t.

[0149] The upper and lower limits of CSP unit output:

[0150]

[0151] In the formula, The minimum technical output of a CSP plant is 30MW. The maximum technical output of a CSP plant is 200MW.

[0152] Thermal storage tank capacity constraints:

[0153]

[0154] In the formula, Represents the minimum and maximum heat storage capacity of the heat storage tank, with values ​​of 0MJ and 6638MJ respectively;

[0155] Climbing constraints of generators in CSP power plants:

[0156]

[0157] In the formula, R is the binary state variable of the unit startup; U / R D are the maximum up and down climbing capabilities of the generator, respectively, and the value is 100MW / h.

[0158] c. Output constraints of thermal power units:

[0159] Thermal power units can be divided into coal-fired power, oil-fired units, gas-fired units, etc. according to the fuel type. Considering the operation safety, thermal power units have maximum and minimum technical output limits and climbing constraints.

[0160] Thermal power operation cost function:

[0161]

[0162] In the formula, f t coal is the total operating cost of the generator set during period t, is the fuel consumption curve; Binary state variable for the unit on / off; represents the startup and shutdown cost of the i-th thermal power unit. The specific values ​​are shown in Table 1.

[0163] The upper and lower limits of thermal power unit output:

[0164] P i,tmin ≤P i,t ≤P i,tmax (17)

[0165] Where P i,tmin / P i,tmax It is the minimum / maximum technical output of thermal power units. The values ​​are shown in Table 1.

[0166] Thermal power unit climbing constraints:

[0167]

[0168] Where P i,t , P i,t+1 represents the output of the i-th thermal power unit during period t and period t+1; ΔP i,up / ΔP i,down is the ramp-up / downward rate of the coal-fired unit, and its values ​​are shown in Table 1.

[0169] d. Hydropower unit output constraints:

[0170] Taking operational safety into consideration, the output of a hydropower unit must change within a certain range in a short period of time during operation, subject to restrictions on reservoir capacity, outflow and inflow, and forced outflow.

[0171] Hydropower operation cost function:

[0172]

[0173] In the formula, f t hydro is the total operating cost of the hydropower unit at time t. j is the function of operation and maintenance cost and output size; Binary state variable for the unit on / off;

[0174] Climbing constraints of hydropower units:

[0175]

[0176] In the formula, is the uphill / downhill rate of the hydropower unit, the values ​​are shown in Table 1, is the output of hydropower unit i at time t;

[0177] Output constraints of hydropower units:

[0178]

[0179] In the formula, Q h (t) is the power generation flow of hydropower unit i in period t; H(t) is the power generation head at time t, which is 39 meters; η G,i The turbine efficiency of hydropower unit i in period t is 80%; η T,i The generator efficiency of hydropower unit i in period t is 80%;

[0180] Power generation flow constraints:

[0181] Q h (t) = min(Q h,out (t),Q h,out,max ) (twenty three)

[0182] In the formula, Q h,out (t) is the outflow capacity of the hydropower unit at time t; Q h,out,max The maximum value of the outbound flow is 0.735m 3 / s;

[0183] Outbound capacity equality constraint:

[0184] Q h,out (t) = Q h (t)+Q h,c (t) (24)

[0185] In the formula, Q h,c (t) is the water limit flow (discarded water flow);

[0186] Storage capacity equality constraint:

[0187] C h (t) = C h (t-1)+Q h,in (t)ΔT-Q h,out (t)ΔT (25)

[0188] In the formula, C h (t) is the storage capacity of the reservoir in period t; Q h,in (t) is the inflow flow of the hydropower unit in period t.

[0189] Outbound traffic constraints:

[0190] 0<Q h,out (t)<Q h,out,max (26)

[0191] In the formula, Q h,out,max is the maximum outbound flow rate;

[0192] C h,min (t)≤C h (t)≤C h,max (t)(27)

[0193] In the formula, C h,max (t) / C h,min (t) is the minimum and maximum storage capacity limit of the reservoir in period t, with values ​​of 140 million cubic meters and 273 million cubic meters respectively.

[0194] e. Nuclear power unit output constraints:

[0195] Operating costs of nuclear power units:

[0196]

[0197] In the formula, f t nuclear is the total operating cost of the hydropower unit at time t, Represents the function of nuclear power operation and maintenance cost and output size; Represents the binary state variable of the on / off of the i-th nuclear power unit during period t; represents the cost of starting up and shutting down the i-th nuclear power unit, and its value is shown in Table 1;

[0198] Nuclear power unit output upper and lower limit constraints:

[0199]

[0200] In the formula, represents the lower and upper limits of the power generation of the i-th nuclear power unit, and its values ​​are shown in Table 1; Represents the output of the i-th nuclear power unit in period t.

[0201] Nuclear power unit climbing constraints:

[0202]

[0203] In the formula, Represents the maximum uphill and downhill capability of the ith nuclear power unit; see Table 1 for its values.

[0204] f. Output constraints of electrochemical energy storage units:

[0205] Energy storage operation cost function:

[0206]

[0207] In the formula, f j (P bat,i+ (t)) represents the operating cost function during the discharge process of the energy storage battery;

[0208] Energy storage capacity constraints:

[0209] 0≤S OCi,t ≤S OCi,max (32)

[0210] In the formula, S OCi,max The maximum capacity of the energy storage battery is 100MW.h, S OCi,t is the battery charge at time t;

[0211] Energy storage capacity balance constraints:

[0212]

[0213] In the formula, Represents the charging / discharging state of the energy storage battery during period t; η c / η d The charging efficiency and discharging efficiency of the energy storage battery are taken as 90%; P bat,i+ (t) represents the power of the energy storage battery during the discharge process of time period t; P bat,i- (t) represents the power of the energy storage battery charging process during period t;

[0214] Energy storage charging and discharging power constraints:

[0215]

[0216] Where: P bat,i+min / P bat,i+max Represents the minimum and maximum power of the energy storage battery during discharge, with values ​​of 0MW and 40MW respectively; P bat,i-min / P bat,i-max Represents the minimum and maximum power of the energy storage battery charging process, with values ​​of 0MW and 40MW respectively.

[0217] g. Output constraints of pumped storage units:

[0218] Pumped storage power station operating costs:

[0219]

[0220] In the formula, Represents the operating cost function of the pumped storage power station during power generation; Represents the three states of pumping, generating electricity, and stopping operation of the i-th generator unit of the pumped storage power station during period t; represents the cost of starting and shutting down the i-th pumped storage unit, which is 500 USD / time;

[0221] Pumped storage unit climbing constraints:

[0222]

[0223] In the formula, ——The pumping and generating power of the i-th unit of the pumped-storage power station during period t; It represents the maximum downhill and uphill capacity of a pumped-storage power station during the pumping process, and its value is 180MW / h.

[0224] Power constraints during pumping and power generation:

[0225]

[0226] In the formula, Represents the minimum and maximum power of the pumping process of the pumped storage power station, with values ​​of 0MW and 180MW respectively; It represents the minimum and maximum power of the pumped storage power station during power generation, and the values ​​are 0MW and 180MW respectively.

[0227] Storage capacity constraints of pumped storage power stations:

[0228]

[0229] S h,min ≤S h,t ≤S h,max (40)

[0230] In the formula, Q h,in (t) / Q h,out (t) represents the inflow and outflow of the warehouse during the period t; η c,cx / η d,cx represents the pumping and power generation efficiency of the pumped storage power station, with values ​​of 85% and 84% respectively; S h,max / S h,min , S h (t) represent the maximum and minimum storage capacity of the pumped storage power station and the pumped storage capacity during period t, with values ​​of 49.4 million cubic meters and 7.17 million cubic meters respectively.

[0231] Furthermore, in a feasible embodiment, a logical variable constraint is also included, using the following expression:

[0232]

[0233] In the formula, Represents the operating status of unit i during period t. When unit i is in the operating state during period t It is the minimum duration of the unit state, that is, the unit must run for a certain time before the state transition can be performed. The values ​​are shown in Table 1.

[0234] Table 1 Conventional unit parameters

[0235]

[0236] In a feasible embodiment, specifically, the detailed process of step S3 is:

[0237] Step S3 solves the model to obtain the reliable predicted output of new energy sources in each period under the most economical operation condition of the power system and includes it in the real-time reserve rate. Figure 3 :

[0238] (1) First, input the data, including grid structure information, unit and operation cost information, wind speed, sunlight, load and other data.

[0239] (2) According to the input wind speed, light intensity, and load, the uncertainty modeling method in step S1 is used to obtain the time series of renewable energy output, load, etc.

[0240] (3) Establish the objective function, equality constraints and inequality constraints described in step S2.

[0241] (4) The CPLEX solver is used to perform a single 168-hour power production simulation calculation.

[0242] (5) Determine the size of the final time period T and the entire production simulation time length of 720 hours.

[0243] (6) If T is less than 720 hours, the on / off status of the unit in the last calculation period T is used as the initial condition of the unit status in the next calculation cycle, and the solution calculation is continued.

[0244] (7) If T is greater than 720 hours, the calculation is completed and the loop exits.

[0245] (8) Output the unit output size and the final optimal calculation result in each period of the entire calculation cycle. According to the calculation, the real-time reserve rate of the reliable output of new energy in each period is obtained.

[0246] The present invention takes the IEEE-24 node system as an example, and replaces some thermal power units with nuclear power, gas-fired power, oil-fired power, hydropower, solar thermal power station, pumped storage power station, wind power, photovoltaic and other power stations in IEEE-GMLC to form an improved 24-node system for simulation calculation. The simulation data of annual wind speed, light, and load and the production simulation model are obtained by step S1 and step S2 to perform power production simulation calculation. The CPLEX solver is used for solution calculation, the solution gap is set to 0.005%, and the upper limit of a single solution time is 1500 seconds. In the calculation, the load reduction cost is set to $500 / MW·h, the wind and light abandonment cost is $50 / MW·h, the pumped storage power station power generation cost is $20 / MW·h, the battery discharge cost is $40 / MW·h, the carbon dioxide treatment cost in the sewage treatment cost is $0.0153 / pound, the sulfur dioxide treatment cost is $25.1 / pound, and the new energy standby cost is the wind and light abandonment cost.

[0247] In order to verify the effectiveness of this method, calculations and analyses are performed under three different schemes:

[0248] Option 1: Calculation cost of operation when new energy is not included in the standby mode;

[0249] Option 2: New energy is included in the operating costs of the reserve at a fixed ratio;

[0250] Option 3: Operating cost of new energy real-time standby at different penetration rates;

[0251] As can be seen from Table 2, when new energy power sources are not included in the system reserve, as the penetration rate of new energy increases, the overall operating cost of the system gradually increases. When the penetration rate of new energy power generation is 50%, although the coal consumption and pollution control costs of thermal power units are low, the cost of power abandonment and load abandonment is almost equivalent to the total operating cost. The total production cost remains high, which is not conducive to the consumption of new energy. With the increase in the penetration rate of new energy in my country's power system, it is necessary to consider incorporating new energy power sources into the system rotating reserve in the new power system.

[0252] Table 2 Simulated operation cost of electricity production under different renewable energy penetration rates when renewable energy is not included in the reserve

[0253]

[0254] Table 3 shows that 5%, 10%, 15%, 20% and 30% of the real-time power generation output of new energy are included in the reserve. Compared with the case where new energy power generation is not considered as a reserve, the total cost increases by 0.53%, 0.711%, 1.3%, 1.52% and 1.32%. With the increase of the reserve ratio, the total cost of system operation shows an upward trend, but the coal consumption cost, energy storage operation cost and switch cost decrease. The main reason for the increase in the total cost of system operation is the increase in the reserve cost of new energy. It can be seen that the economic efficiency of including new energy in the reserve at a fixed ratio is poor, and the higher the reserve rate of new energy, the worse the system economy. Therefore, choosing a suitable proportion of new energy to be included in the reserve and a reasonable way to include it in the reserve is particularly important for the economic efficiency of system operation.

[0255] Table 3 Simulated operation cost of power production when new energy is incorporated into reserve at different fixed ratios

[0256]

[0257] As can be seen from Table 4, with the increase in the penetration rate of new energy, the energy storage operation cost and the cost of starting and stopping the unit will increase significantly. This is because the increase in the penetration rate of new energy increases the uncertainty and volatility of system operation, but the capacity of new energy as a backup is also larger, the utilization hours of thermal power units in the system will decrease, and the coal consumption cost and pollution emissions will decrease accordingly.

[0258] Table 4 Production simulation operation cost of new energy real-time standby under different penetration rates

[0259]

[0260] Compared with the situation in Table 2 where new energy backup is not considered, as the penetration rate of new energy continues to increase, the cost reduction degree when new energy is included in the backup becomes more and more obvious. When the penetration rate of new energy power generation is 15%, 20%, 25%, 30%, 40%, and 50%, respectively, the total operating cost obtained by the method of new energy real-time backup of the present invention will be reduced by -15.48%, -8.09%, -8.35%, 9.66%, 54.72%, and 84.87%, respectively. Figure 4 , is a real-time reserve rate diagram of the invention when the new energy penetration rate is 30% and the new energy generation is included in the system reserve for 720h. It can be seen that when the new energy penetration rate is lower than 30%, the economic efficiency of incorporating new energy into the reserve operation is not good, but when the new energy penetration rate is above 30%, the inclusion of new energy into the real-time reserve plays an important role in improving the economic efficiency of operation. In the new power system with new energy as the main body, the economic efficiency of the method of the invention will be better and better.

Claims

1. A method for determining the real-time reserve rate of new energy power sources in medium and long time scales, characterized in that: The following steps are involved: S1. Obtaining the uncertain time sequence output of new energy. The step S1 includes the following steps: S101. Sampling historical data to establish a randomness and uncertainty model for new energy; S102. Using the k-medoids clustering method to replace the same or similar scenarios with representative scenarios to eliminate data redundancy; S103. Considering the impact of errors and uncertainties, the final predicted time series output is obtained; S2, establishing a multi-source power production simulation model including new energy power sources; the step S2 specifically includes: taking the production simulation cost optimization as the goal, considering the output characteristics and output constraints of various units in the system, power balance constraints and the reserve constraints of incorporating new energy into the system reserve at the real-time reserve rate, establishing a production simulation model; the step S2 includes the following steps: S201, the production simulation cost includes the operating cost, startup and shutdown cost, pollution control cost, and new energy power abandonment penalty cost and load shedding penalty cost of the generator set, and specifically includes the following steps: A. Use the following formula to calculate the overall system operating cost f1: In the formula, f t is the operating cost function of various units in period t; RC , Respectively represent the penalty coefficient for abandoned power of new energy and the amount of abandoned power of new energy; λ LC , Represent the load shedding penalty coefficient and load shedding power respectively; λ Ci,t , S i,t They represent the pollution control cost and pollution discharge corresponding to the power generation of the i-th generator in period t respectively; B. Use the following formula to calculate the operating cost function f of each type of unit during period t t : In the formula, f j (P i,t ) is the function of the unit operation and maintenance cost and output size; Binary state variable for the unit on / off; represents the startup and shutdown cost of the i-th unit; C. Use the following formula to calculate the amount of abandoned new energy In the formula, It represents the maximum power output of the wind farm during period t; Indicates the real-time output of wind farm dispatch during period t; It represents the maximum power output of the photovoltaic power plant during period t; Indicates the real-time output of the photovoltaic power field during period t; D. Use the following formula to calculate the load shedding power In the formula, Indicates the real-time load of the system; P load Indicates the load involved in scheduling balance; S202, the output constraints of various units in the system are expressed as: a. Output constraints of wind power and photovoltaic units: In the formula, Represents the maximum output of the wind turbine during period t; Represents the maximum output of photovoltaic power generation during period t; b. Output constraints of CSP units: The output constraints of the CSP unit include the dynamic balance constraint of the heat of the collector field, the dynamic balance constraint of the heat of the heat storage tank, the upper and lower limit constraints of the generator output, and the climbing constraint: Dynamic balance constraints of heat in the collector field: In the formula, They are the heat used by the CSP station for power generation during period t, the total solar heat absorbed by the collector field, the heat stored in the heat tank by the CSP station, and the heat abandoned by the CSP station; The thermal efficiency of the collector field in absorbing heat and transferring it to power generation; Dynamic balance constraints of heat storage tank: In the formula, They are the heat stored in the heat tank, the heat transferred from the collector field to the heat storage tank, and the heat transferred from the heat storage tank to the power generation side during period t. The heat storage efficiency of the heat storage tank; Thermoelectric conversion efficiency constraints: In the formula, The power generation efficiency of the CSP station; The power output of the CSP station at time t; Upper and lower limits of power generation output of CSP stations: In the formula, Provide the minimum technical contribution for CSP power stations; Provide the greatest technical contribution to CSP plants; Thermal storage tank capacity constraints: In the formula, Represents the minimum and maximum heat storage capacity of the heat storage tank; Climbing constraints of generators in CSP power plants: In the formula, R is the binary state variable of the unit startup; U / R D are the maximum up and down climbing capabilities of the generator respectively; c. Output constraints of thermal power units: The output constraints of thermal power units include maximum and minimum technical output constraints and ramp constraints; Output upper and lower limits of thermal power units: P i,tmin ≤P i,t ≤P i,tmax Where P i,tmin / P i,tmax The minimum / maximum technical output of thermal power units; Thermal power unit climbing constraints: Where P i,t , P i,t+1 represents the output of the i-th thermal power unit in period t and period t+1; ΔP i,up / ΔP i,down is the ramp-up / down ramp rate of the coal-fired unit; d. Hydropower unit output constraints: Output equation constraints of hydropower units: In the formula, is the output of hydropower unit i at time t, Q h (t) is the power generation flow of hydropower unit i in period t; H(t) is the power generation head at time t; η G,i is the turbine efficiency of hydropower unit i in period t; η T,i is the generator efficiency of hydropower unit i in period t; Among them, the power generation flow constraint is: Q h (t) = min(Q h,out (t),Q h,out,max ), Q h,out (t) is the outflow capacity of the hydropower unit at time t; Q h,out,max is the maximum outbound flow rate; Outbound capacity equality constraint: Q h,out (t) = Q h (t)+Q h,c (t), Q h,c (t) is the water flow limit; Outbound flow upper and lower limit constraints: 0<Q h,out (t)<Q h,out,max , Q h,out,max is the maximum outbound flow rate; Storage capacity equality constraint: C h (t) = C h (t-1)+Q h,in (t)ΔT-Q h,out (t)ΔT,C h (t) is the storage capacity of the reservoir in period t; Q h,in (t) is the inflow flow of the hydropower unit in period t; Maximum and minimum storage capacity constraints: C h,min (t)≤C h (t)≤C h,max (t), C h,max (t) / C h,min (t) is the maximum / minimum storage capacity limit of the reservoir in period t; Climbing constraints of hydropower units: In the formula, is the uphill / downhill rate of the hydropower unit, is the output of hydropower unit i at time t; e. Nuclear power unit constraints: Nuclear power unit output upper and lower limit constraints: In the formula, Represents the lower and upper limits of the power generation of the i-th nuclear power unit; represents the output of the i-th nuclear power unit during period t; Nuclear power unit climbing constraints: In the formula, represents the maximum uphill and downhill capability of the i-th nuclear power unit; f. Constraints of electrochemical energy storage units: Energy storage capacity upper and lower limits: 0≤S OCi,t ≤S OCi,max In the formula, S OCi,max , S OCi,t are the maximum capacity of the energy storage battery and the battery charge at time t respectively; Energy storage capacity balance constraints: In the formula, Represents the charging / discharging state of the energy storage battery during period t; P bat,i+ (t) represents the power of the energy storage battery during the discharge process of time period t; P bat,i- (t) represents the power of the energy storage battery charging process during period t; η c / η d Energy storage battery charging efficiency and discharging efficiency; Energy storage charging and discharging power constraints: Where: P bat,i+min / P bat,i+max Represents the minimum and maximum power of the energy storage battery during discharge; P bat,i-min / P bat,i-max Represents the minimum and maximum power of the energy storage battery charging process; g. Pumped storage unit constraints: Pumped storage unit climbing constraints: In the formula, is the pumping and generating power of the i-th unit of the pumped storage power station during period t; Represents the maximum downhill and uphill capacity of a pumped storage power station during pumping; Power constraints during pumping and power generation: In the formula, Represents the minimum and maximum power of the pumping process of the pumped storage power station; Represents the minimum and maximum power of the power generation process of the pumped storage power station; Pumped storage power station storage capacity constraints: In the formula, Q h,in (t) / Q h,out (t) represents the inflow and outflow of the warehouse during the period t; η c,cx / η d,cx Represents the pumping and power generation efficiency of the pumped storage power station; S h,max / S h,min , S h (t) represents the maximum and minimum storage capacity of the pumped storage power station and the pumped storage capacity during period t, respectively; They represent the inbound and outbound traffic status during period t respectively; S203, the power balance constraint is expressed as follows: In the formula, They represent the coal-fired power generation, oil-fired power generation, gas-fired power generation, hydropower generation, nuclear power generation, solar thermal power station generation, pumped storage power station generation, photovoltaic power generation, wind power generation, energy storage charging and discharging power, and new energy curtailment power during period t respectively; They represent the load power, battery charging power, pumped storage power, and load shedding power in period t respectively; S204, the backup constraint is expressed as follows: Where P i,max (i, t) represents the maximum allowable output of unit i during period t; P(i, t) represents the real-time power generation output of unit i during period t; represents the operating status of unit i during period t; β t is the real-time reserve rate of renewable energy power generation, η is the reliable prediction accuracy of renewable energy power generation; P re,t represents the spinning reserve capacity of the system during period t; S205, also includes logical variable constraints, expressed as follows: In the formula, Represents the operating status of unit i during period t. When unit i is in the operating state during period t The minimum duration of the unit's operating state, that is, the unit must run for a certain period of time before the state transition can be performed; S3. Solve the multi-source power production simulation model of step S2 to obtain the real-time reserve rate of the reliable predicted output of new energy in each time period.

2. The method for determining the real-time standby rate of new energy power sources in the medium and long time scale according to claim 1 is characterized in that: The step S3 specifically includes: solving the multi-source power production simulation model obtained in step S2, obtaining the reliable predicted output of new energy in each time period under the most economical condition of the power system operation, incorporating the real-time reserve rate, incorporating the new energy in each time period into the power system reserve according to the obtained real-time reserve rate, and obtaining the output of each unit in each time period under the optimal target.

3. The method for determining the real-time standby rate of new energy power sources in the medium and long time scale according to any one of claims 1 to 2, characterized in that: The multi-source power production simulation model solving method is to solve it by calling the CPLEX solver through MATLAB.

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