Two-stage robust unit combination method considering multi-class power supply standby collaborative optimization

Abstract

The invention provides a two-stage robust unit commitment method considering multi-class power supply standby collaborative optimization, a day-ahead-intra-day two-stage robust unit commitment model considering multi-class resource standby collaborative optimization is constructed, and collaborative optimal determination of a unit commitment (UC) scheme and standby capacity under all types of equipment is realized. The model can accurately quantify the system reserve capacity required for coping with the wind power uncertainty, and reasonably distributes the reserve capacity for various resources and equipment in each link of source network load storage. On the premise of ensuring the operation safety of the system and the equipment, the model realizes the collaborative optimization of the UC scheme and the reserve capacity, so that the economy and the reliability of the system operation are improved.

Description

Technical Field

[0001] The invention relates to the technical field of power systems, and in particular to a two-stage robust unit combination method considering coordinated optimization of multiple types of power reserve. Background Art

[0002] The backup resources in the new power system are no longer limited to traditional synchronous power generation resources. Pumped storage units, electrochemical energy storage equipment, demand-side response, and cross-regional interconnection lines can all be used as flexible backup resources. However, due to the large differences in the characteristics of these devices, it is relatively difficult to construct a collaborative optimization model of UC solutions and backup capacity that takes into account multiple types of resources and equipment, and no relevant research reports have been reported so far. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a two-stage robust unit combination method considering the coordinated optimization of multiple types of power reserve, to achieve the coordinated optimization of UC scheme and reserve capacity, thereby improving the economy and reliability of system operation.

[0004] To achieve the above-mentioned purpose, the present invention adopts the following technical solutions: a two-stage robust unit commitment method considering the coordinated optimization of multiple types of power reserve, a UC scheme considering multiple resources and equipment of source, grid, load and storage, and a two-stage robust optimization model for coordinated reserve capacity;

[0005]

[0006] X={x|Ax≥b} (2)

[0007]

[0008] Among them, X is the feasible domain of the first-stage variables; x is the first-stage variable; U is the wind power uncertainty set; w is the uncertainty variable of the actual available wind power; is the feasible domain of the second-stage variables after the first-stage variables x and the actual available wind power w are given; y and z are the second-stage continuous variables and 0-1 integer variables respectively; c, d, g, A, b, E, G, f, R, D, T, and v are the constant matrices of the objective function and constraints respectively.

[0009] In a preferred embodiment, the objective function of the first stage is to minimize the sum of the operation and standby costs of various resources and equipment under the scenario of wind power available power predicted on the day before;

[0010]

[0011] Among them, N G is the total number of thermal power units; are the operating cost, startup cost, minimum technical output cost, and reserved standby cost of thermal power unit g, respectively. The unit operating cost is a piecewise linear function related to the output range of each unit and the corresponding energy price; p g,t ,y g,t 、x g,t , are the output, startup status, operation status, positive reserve capacity, and negative reserve capacity of thermal power unit g in period t; N H is the total number of hydropower units; Reserved standby cost for hydropower unit h; are the positive and negative reserve capacities of hydropower unit h in time period t, respectively; is the total number of pumped storage units; Reserved reserve costs for pumped storage units; are the positive and negative reserve capacities of pumped storage unit s in time period t, respectively; is the total number of chemical energy storage devices; Reserved reserve costs for chemical energy storage equipments; are the positive and negative reserve capacities of chemical energy storage device s in time period t, respectively; is the total number of communication lines; Reserved standby fee for the AC line o; are respectively the positive and negative reserve capacities of the AC tie line o in time period t; is the total number of DC tie lines; Reserved reserve cost for DC tie line o; are respectively the positive and negative reserve capacities of DC tie line o in period t; N D is the total number of load nodes; is the reserve cost for load d; r d,t is the reserve capacity of load d participating in demand-side response in period t.

[0012] In a preferred embodiment, the system power balance constraint in the first stage is:

[0013]

[0014] Among them, p h,t is the output of hydropower unit h in period t; p r,t is the output of wind turbine r in period t; are respectively the power generation and pumping power of pumped storage unit s in time period t; are the discharge and charge powers of chemical energy storage device s in time period t, respectively; is the transmission power of the AC tie line o in time period t; is the transmission power of DC tie line o in time period t; p d,t is the load demand of load d in time period t.

[0015] In a preferred embodiment, the thermal power generation unit constraints of the first stage are:

[0016]

[0017] Among them, z g,t is the shutdown state of thermal power unit g in period t; TU g , TD g are the minimum continuous start and stop time of thermal power unit g respectively; are the maximum and minimum technical outputs of thermal power unit g respectively; ΔT is the duration of a single dispatch period; They are the up and down climbing rates of thermal power unit g respectively.

[0018] In a preferred embodiment, the hydropower unit constraints of the first stage are:

[0019]

[0020]

[0021] Among them, x h,t is the operating status of hydropower unit h in time period t; are the maximum and minimum technical outputs of hydropower unit h, respectively; H(j) is the set of hydropower units h equipped in reservoir j; η h is the water-to-electricity conversion efficiency of the hydropower unit; ρ is the density of water; g is the acceleration of gravity; h j is the net head height of reservoir j. The change of net head height is usually small and can be assumed to be a fixed value; is the power generation flow of hydropower unit h in time period t; are the maximum and minimum power generation flow of hydropower unit h respectively; is the outflow (discharge) flow of reservoir j in period t; is the water discharge of reservoir j in period t; are the maximum and minimum outflows of reservoir j respectively; are the maximum and minimum water discharge of reservoir j respectively; I(j) is the set of upstream reservoirs i of reservoir j; vj ,t is the storage capacity of reservoir j in time period t; is the predicted natural water flow of reservoir j in period t; α i is the water loss rate from reservoir i to reservoir j; τ iis the time lag of water flow from reservoir i to reservoir j; are the maximum and minimum storage capacities of reservoir j respectively.

[0022] In a preferred embodiment, the wind turbine constraints in the first stage are:

[0023]

[0024] In the formula, is the predicted available power of wind farm r in period t;

[0025] 6) Nuclear power plant constraints

[0026]

[0027] in, are the state variables of the A operation mode and G operation mode of the nuclear power unit n, respectively. In the A mode, the nuclear power unit does not participate in the peak load regulation and maintains the rated power operation. In the G mode, the nuclear power unit participates in the peak load regulation and adopts a specific daily load tracking mode. n,t is the output of nuclear power unit n in time period t; is the rated power of nuclear power unit n; is the daily load following mode output curve adopted by nuclear power unit n;

[0028] The constraints of the pumped storage units in the first stage are:

[0029]

[0030] in, are the power generation and pumping state variables of pumped storage unit s in time period t, respectively; are the maximum and minimum technical outputs of pumped storage unit s under power generation conditions; are the pumping power of the pumped storage unit s respectively. When the pump turbine is in the pumping state, its guide vane is fixed at the optimal opening, and the active power absorbed from the system is generally the rated value; is the virtual power generation of pumped storage unit s in time period t, which is positive under power generation conditions and negative under pumping conditions; are the water-to-electricity conversion coefficients of the pumped storage unit s under power generation and pumping conditions respectively; are the power generation flow and pumping flow of pumped storage unit s in time period t respectively;

[0031] are the maximum and minimum limits of power generation flow of pumped storage unit s, respectively; is the rated value of pumped storage unit s’ pumping flow; S(j) is the set of pumped storage units s equipped in reservoir j; is the outflow of reservoir j in period t; v j,t is the remaining storage capacity of reservoir j in period t; are the maximum and minimum remaining capacities allowed for reservoir j during the scheduling process.

[0032] In a preferred embodiment, the chemical energy storage device of the first stage is constrained by:

[0033]

[0034] in, are the discharging and charging operating states of the chemical energy storage device s in time period t, respectively; are the maximum discharge and charge powers of chemical energy storage device s, respectively; is the virtual power generation of the chemical energy storage device s in time period t, which is positive under discharge conditions and negative under charge conditions; is the charge and discharge efficiency of chemical energy storage device s; is the remaining capacity of the chemical energy storage device s in time period t; are the maximum and minimum remaining capacities allowed for chemical energy storage equipment s in the scheduling process;

[0035] The AC tie line constraints of the first phase are:

[0036]

[0037] in, are the positive and reverse power flow transmission limits of the AC tie line o respectively; is the planned transmission power value of the AC interconnection line o in time period t obtained by decomposition according to the long-term contract;

[0038] The DC tie line constraints of the first stage are:

[0039]

[0040] Among them, x o,t is the operating state of the DC tie line o in time period t; The forward and reverse power flow transmission limits of the DC tie line o respectively; are the power rise and fall rate limits of tie line o respectively; They are the forward and reverse adjustment states of tie line o in time period t respectively; are auxiliary variables respectively; is the planned transmission power value of the DC tie line o in time period t obtained by decomposing it according to the long-term contract;

[0041] The load demand response constraints of the first stage are:

[0042]

[0043] In the formula, is the predicted load demand of load d in period t; is the maximum value of the demand-side response reserve of load d in period t;

[0044] The branch flow constraints in the first stage are:

[0045]

[0046] In the formula, are the forward and reverse power flow transmission limits of branch l respectively; F g-l 、F h-l 、F r-l , F d-l They are the power flow transfer distribution factors of the thermal power unit g, hydropower unit h, wind power unit r, pumped storage unit s, chemical energy storage equipment s, the end point on one side of the AC interconnection line o, the end point on one side of the DC interconnection line o, and the node where the load d is located to the line l.

[0047] In a preferred embodiment, the objective function of the second stage is as follows: the second stage is a two-layer optimization problem, the inner layer problem objective is to minimize the sum of the cost of calling multiple resource reserves, the penalty cost of wind abandonment and the penalty cost of load shedding under a given wind power available power scenario, and the specific objective function is:

[0048]

[0049] Among them, the superscript ^ indicates the second-stage variables; The cost of calling thermal power unit g for standby; is the positive and negative reserve capacity of thermal power unit g called in time period t; Costs for calling up the hydropower unit g for standby; are respectively the positive and negative reserve capacity of hydropower unit h called in time period t; Costs for calling pumped storage units for standby; are respectively the positive and negative reserve capacity of the pumped storage unit s called in time period t; Costs for calling chemical energy storage equipment for standby; are respectively the positive and negative reserve capacity of chemical energy storage device s called in time period t; Costs for calling up the AC line for standby; are respectively the positive and negative reserve capacity of the AC tie line o called in time period t; Costs for calling up the DC interconnection line for backup; are respectively the positive and negative reserve capacity of DC tie line o called in time period t; The cost of calling up the load reserve; is the reserve capacity called for load d; is the penalty fee for wind turbine r’s wind abandonment; is the wind abandonment volume of wind turbine r in period t; is the load shedding penalty cost of load d; is the load shedding amount of load d in time period t;

[0050] The output and reserve adjustment constraints of thermal power units in the second phase are:

[0051]

[0052] in, is the output of the thermal power unit g in the second stage during period t;

[0053] The output and reserve adjustment constraints of the hydropower units in the second phase are as follows:

[0054]

[0055] in, is the output of hydropower unit h in period t in the second stage.

[0056] In a preferred embodiment, the wind turbine abandonment constraint in the second stage is:

[0057]

[0058] in, is the output of wind turbine r in the second stage during period t; w r,t is the actual available power of wind farm r in the second stage during period t, w r,t The uncertainty of is described by the uncertainty set U;

[0059] The output adjustment constraints of nuclear power in the second phase are:

[0060]

[0061] in, is the output of the second-stage nuclear power unit n in time period t; due to the safety technical requirements of nuclear power units, the second-stage output of nuclear power units usually adopts the day-ahead planned output to avoid the impact of frequency regulation on unit performance;

[0062] The output and reserve adjustment constraints of the pumped storage units in the second stage are:

[0063]

[0064] in, They are respectively the generating power and pumping power of the pumped storage unit s in the second stage during time period t.

[0065] In a preferred embodiment, the output and reserve adjustment constraints of the chemical energy storage equipment in the second stage are:

[0066]

[0067] in, are the discharge and charge powers of the chemical energy storage device s in the second stage in time period t, respectively;

[0068] The AC tie line output and reserve adjustment constraints in the second phase are:

[0069]

[0070] in, is the output of the second-stage AC tie line o in time period t;

[0071] The DC tie line output and reserve adjustment constraints in the second phase are:

[0072]

[0073] in, is the output of the DC tie line o in the second stage in time period t;

[0074] The load demand response and load shedding constraints in the second stage:

[0075]

[0076] in, is the load of the second stage load d in time period t; It is the demand-side reserve capacity that the second-stage load d can continue to provide after participating in demand response in period t.

[0077] Compared with the prior art, the present invention has the following beneficial effects: The present invention constructs a two-stage day-ahead and intraday robust unit commitment model that considers the coordinated optimization of multiple types of resource reserves, aiming to achieve the coordinated optimal determination of unit combination (UC) schemes and reserve capacity under all types of equipment. The model can accurately quantify the system reserve capacity required to cope with wind power uncertainty, and reasonably allocate reserve capacity for various resources and equipment in each link of source, grid, load and storage. Under the premise of ensuring the safety of system and equipment operation, the model realizes the coordinated optimization of UC schemes and reserve capacity, thereby improving the economy and reliability of system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1Schematic diagram of the NC&CG algorithm flow chart of the preferred embodiment of the present invention. DETAILED DESCRIPTION

[0079] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0080] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0081] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations.

[0082] The UC solution and the two-stage robust optimization model of spare capacity coordination considering multiple resources and equipment of source, grid, load and storage constructed by this method can be written in the following compact form:

[0083]

[0084] X={x|Ax≥b} (2)

[0085]

[0086] in, is the feasible domain of the first-stage variables; x is the first-stage variables; U is the wind power uncertainty set; w is the uncertainty variable of the actual available wind power; is the feasible domain of the second-stage variables after the first-stage variables x and the actual available wind power w are given; y and z are the second-stage continuous variables and 0-1 integer variables respectively; c, d, g, A, b, E, G, f, R, D, T, and v are the constant matrices of the objective function and constraints respectively.

[0087] 1. First stage optimization model

[0088] (8) The first stage model in the model is as follows:

[0089] 1) Objective function: The objective function of the first stage is to minimize the sum of the operating and standby costs of various resources and equipment under the scenario of wind power available power forecasted on the day before. The operating cost in this method mainly focuses on the operating cost of thermal power units, ignoring the operating costs of other resources such as hydropower, nuclear power, pumped storage, and energy storage. In practical applications, the operating costs of other equipment can be easily expanded.

[0090]

[0091] Among them, N G is the total number of thermal power units; are the operating cost, startup cost, minimum technical output cost, and reserved standby cost of thermal power unit g, respectively. The unit operating cost is a piecewise linear function related to the output range of each unit and the corresponding energy price; p g,t ,y g,t 、x g,t , are the output, startup status, operation status, positive reserve capacity, and negative reserve capacity of thermal power unit g in period t; N H is the total number of hydropower units; Reserved standby cost for hydropower unit h; are the positive and negative reserve capacities of hydropower unit h in time period t, respectively; is the total number of pumped storage units; Reserved reserve costs for pumped storage units; are the positive and negative reserve capacities of pumped storage unit s in time period t, respectively; is the total number of chemical energy storage devices; Reserved reserve costs for chemical energy storage equipments; are the positive and negative reserve capacities of chemical energy storage device s in time period t, respectively; is the total number of communication lines; Reserved standby fee for the AC line o; are respectively the positive and negative reserve capacities of the AC tie line o in time period t; is the total number of DC tie lines; Reserved reserve cost for DC tie line o; are respectively the positive and negative reserve capacities of DC tie line o in period t; N D is the total number of load nodes; is the reserve cost for load d; r d,t is the reserve capacity of load d participating in demand-side response in period t.

[0092] 2) System power balance constraints

[0093]

[0094] Among them, p h,t is the output of hydropower unit h in period t; p r,t is the output of wind turbine r in period t; are respectively the power generation and pumping power of pumped storage unit s in time period t; are the discharge and charge powers of chemical energy storage device s in time period t, respectively; is the transmission power of the AC tie line o in time period t (incoming is positive, outgoing is negative); is the transmission power of the DC tie line o in time period t (incoming is positive, outgoing is negative); p d,t is the load demand of load d in time period t.

[0095] 3) Constraints on thermal power units

[0096]

[0097] Among them, z g,t is the shutdown state of thermal power unit g in period t; TU g , TD g are the minimum continuous start and stop time of thermal power unit g respectively; are the maximum and minimum technical outputs of thermal power unit g respectively; ΔT is the duration of a single dispatch period; are the up and down ramp rates of thermal power unit g respectively; Formula (11)-(12) are the start and stop constraints of thermal power units; Formula (13)-(14) are the minimum start and stop time constraints of thermal power units; Formula (15) is the output constraint of thermal power units; Formula (16)-(17) consider the up and down ramp constraints of thermal power units. Formula (18) is the reserve capacity constraint of thermal power units.

[0098] 4) Constraints on hydropower units

[0099]

[0100]

[0101] Among them, x h,t is the operating status of hydropower unit h in time period t; are the maximum and minimum technical outputs of hydropower unit h, respectively; H(j) is the set of hydropower units h equipped in reservoir j; η h is the water-to-electricity conversion efficiency of the hydropower unit; ρ is the density of water; g is the acceleration of gravity; h j is the net head height of reservoir j. The change of net head height is usually small and can be assumed to be a fixed value; is the power generation flow of hydropower unit h in time period t; are the maximum and minimum power generation flow of hydropower unit h respectively; is the outflow (discharge) flow of reservoir j in period t; is the water discharge of reservoir j in period t; are the maximum and minimum outflows of reservoir j respectively; are the maximum and minimum water discharge of reservoir j, respectively; I(j) is the set of upstream reservoirs i of reservoir j; v j,t is the storage capacity of reservoir j in time period t; is the predicted natural water flow of reservoir j in period t; α i is the water loss rate from reservoir i to reservoir j; τ i is the time lag of water flow from reservoir i to reservoir j; are the maximum and minimum storage capacities of reservoir j respectively; formula (19) is the maximum and minimum technical output constraints of the hydropower unit; formula (20) is the reserve capacity constraint of the hydropower unit; formula (21) is the simplified function of the hydropower unit's power generation; formula (22) is the power generation flow constraint of the hydropower unit; formulas (23)-(25) are reservoir flow constraints; formulas (26)-(28) are reservoir capacity constraints, among which formula (27) prevents excessive water discharge from the reservoir, which is conducive to maintaining stable power generation of the hydropower unit; formula (28) ensures that the reservoir capacity is equal at the beginning and end of the dispatch, which is conducive to the cyclic dispatch of the hydropower unit.

[0102] Since hydropower units can usually be started or stopped in a short time and their output levels can be adjusted quickly, this method does not consider their minimum start-stop time and ramp rate constraints.

[0103] 5) Wind turbine constraints

[0104]

[0105] In the formula, is the predicted available power of wind farm r in time period t.

[0106] 6) Nuclear power plant constraints

[0107]

[0108] in, are the state variables of the A operation mode and G operation mode of the nuclear power unit n, respectively. In the A mode, the nuclear power unit does not participate in the peak load regulation and maintains the rated power operation. In the G mode, the nuclear power unit participates in the peak load regulation and adopts a specific daily load tracking mode. n,t is the output of nuclear power unit n in time period t; is the rated power of nuclear power unit n; It is the daily load tracking mode output curve adopted by nuclear power unit n, such as "12-3-6-3", "15-1-7-1" and other output modes.

[0109] 7) Constraints on pumped storage units

[0110]

[0111] in, are the power generation and pumping state variables of pumped storage unit s in period t, respectively; are the maximum and minimum technical outputs of pumped storage unit s under power generation conditions; are the pumping power of the pumped storage unit s respectively. When the pump turbine is in the pumping state, its guide vane is fixed at the optimal opening, and the active power absorbed from the system is generally the rated value; is the virtual power generation of pumped storage unit s in time period t, which is positive under power generation conditions and negative under pumping conditions; are the water-to-electricity conversion coefficients of the pumped storage unit s under power generation and pumping conditions respectively; are the power generation flow and pumping flow of pumped storage unit s in time period t respectively; are the maximum and minimum limits of power generation flow of pumped storage unit s, respectively; is the rated value of pumped storage unit s’ pumping flow; S(j) is the set of pumped storage units s equipped in reservoir j; is the outflow of reservoir j in period t; v j,t is the remaining storage capacity of reservoir j in period t; are the maximum and minimum remaining capacities allowed by reservoir j during the dispatching process; formula (33) is the power generation and pumping operation constraints of the pumped storage unit; formula (34) is the maximum and minimum technical output constraints of the pumped storage unit; formula (35) is the pumping power constraint of the pumped storage unit; formula (36) is the virtual power generation constraint of the pumped storage unit; formula (37) is the spare capacity constraint of the pumped storage unit; formulas (38)-(39) are simplified functions of the power generation of the pumped storage unit; formulas (40)-(41) are the power generation and pumping flow constraints of the pumped storage unit; formulas (42)-(44) are reservoir capacity constraints.

[0112] Since pumped storage units can usually switch operating conditions in a short time and adjust their output levels quickly, this method does not consider their minimum start-stop time and ramp rate constraints.

[0113] 8) Constraints on chemical energy storage devices

[0114]

[0115] in, are the discharging and charging operating states of the chemical energy storage device s in time period t, respectively; are the maximum discharge and charge powers of chemical energy storage device s, respectively; is the virtual power generation of the chemical energy storage device s in time period t, which is positive under discharge conditions and negative under charge conditions; is the charge and discharge efficiency of chemical energy storage device s; is the remaining capacity of the chemical energy storage device s in time period t; are the maximum and minimum remaining capacities allowed for chemical energy storage equipment s during the scheduling process; formula (45) is the operation constraint of energy storage; formulas (46)-(47) are the charging and discharging power constraints of energy storage; formula (48) is the virtual output constraint of energy storage; formula (49) is the spare capacity constraint of energy storage; formulas (50)-(52) are the remaining capacity constraints of energy storage equipment, among which formula (51) prevents excessive charging and discharging of energy storage, which is beneficial to extending the service life of energy storage; formula (52) ensures that the capacity of energy storage is equal at the beginning and end of scheduling, which is beneficial to the cyclic scheduling of energy storage.

[0116] Since chemical energy storage equipment can usually switch operating conditions in a short time and can quickly adjust its output level, this method does not consider its minimum start-stop time and ramp rate constraints.

[0117] 9) Communication line constraints

[0118]

[0119] in, are the positive and reverse power flow transmission limits of the AC tie line o respectively; is the planned transmission power value of the AC interconnection line o in time period t obtained by decomposing the long-term contract; formula (53) is the transmission power constraint of the interconnection line; formula (54) is the spare capacity constraint of the interconnection line; formula (55) is the planned transmission power constraint of the interconnection line.

[0120] 10) DC tie line constraints

[0121]

[0122]

[0123] Among them, x o,t is the operating state of the DC tie line o in time period t; The forward and reverse power flow transmission limits of the DC tie line o respectively; are the power rise and fall rate limits of tie line o respectively; They are the forward and reverse adjustment states of tie line o in time period t respectively; are auxiliary variables respectively; is the planned transmission power value of the DC tie line o in time period t obtained by decomposing the long-term contract; Formula (56) is the tie line transmission power constraint; Formula (57) is the tie line spare capacity constraint; Formulas (58)-(59) are the tie line power adjustment rate constraints; (60)-(66) ensure that the tie line power cannot be adjusted reversely in adjacent time periods, which is beneficial to extending the service life of the high-voltage DC converter equipment; Formula (67) is the planned transmission power constraint of the tie line.

[0124] 11) Load demand response constraints

[0125]

[0126] In the formula, is the predicted load demand of load d in period t; is the maximum value of the demand-side response reserve of load d in period t.

[0127] 12) Branch flow constraints

[0128]

[0129] In the formula, are the forward and reverse power flow transmission limits of branch l respectively; F g-l 、F h-l 、F r-l , F d-l They are the power flow transfer distribution factors of the thermal power unit g, hydropower unit h, wind power unit r, pumped storage unit s, chemical energy storage equipment s, the end point on one side of the AC interconnection line o, the end point on one side of the DC interconnection line o, and the node where the load d is located to the line l.

[0130] 2 Second stage optimization model

[0131] The second stage is to further adjust the decisions of the first stage according to the actual available power of wind power after the start and stop, output and spare capacity of the first stage are known, so as to ensure that when the actual wind power value deviates from the forecast value on the day before, the unit has sufficient spare capacity to adjust the output and ensure the power balance of the system. Among them, the start and stop of thermal power units are usually determined on the day before (first stage optimization), while the start and stop and operating conditions of hydropower, pumped storage and energy storage equipment are more flexible and can be adjusted in the second stage (intraday).

[0132] The second stage model in equations (6)-(8) is as follows:

[0133] 1) Objective function: The second stage is a two-layer optimization problem. The inner problem objective is to minimize the sum of the cost of calling multiple resource reserves, the penalty cost of wind abandonment and the penalty cost of load shedding under a given wind power available power scenario (in order to avoid load shedding as much as possible, the penalty can be set relatively large). The outer problem objective is to search for the worst wind power available power scenario in the uncertainty set that maximizes the value of the inner problem objective function. The specific objective function is:

[0134]

[0135] Among them, the superscript ^ indicates the second-stage variables; The cost of calling thermal power unit g for standby; is the positive and negative reserve capacity of thermal power unit g called in time period t; Costs for calling up the hydropower unit g for standby; are respectively the positive and negative reserve capacity of hydropower unit h called in time period t; Costs for calling pumped storage units for standby; are respectively the positive and negative reserve capacity of the pumped storage unit s called in time period t; Costs for calling chemical energy storage equipment for standby; are respectively the positive and negative reserve capacity of chemical energy storage device s called in time period t; Costs for calling up the AC line for standby; are respectively the positive and negative reserve capacity of the AC tie line o called in time period t; Costs for calling up the DC interconnection line for backup; are respectively the positive and negative reserve capacity of DC tie line o called in time period t; The cost of calling up the load reserve; is the reserve capacity called for load d; is the penalty fee for wind turbine r’s wind abandonment; is the wind abandonment volume of wind turbine r in period t; is the load shedding penalty cost of load d; is the load shedding amount of load d in time period t;

[0136] 2) Constraints on output and reserve adjustment of thermal power units

[0137]

[0138]

[0139] in, is the output of thermal power unit g in the second stage during period t.

[0140] 3) Hydropower unit output and reserve adjustment constraints

[0141]

[0142] in, is the output of hydropower unit h in period t in the second stage.

[0143] 4) Wind turbine abandonment constraints

[0144]

[0145] in, is the output of wind turbine r in the second stage during period t; w r,t is the actual available power of wind farm r in the second stage during period t, w r,t The uncertainty of is described by the uncertainty set U.

[0146] 5) Output adjustment constraints of nuclear power

[0147]

[0148] in, is the output of the second-stage nuclear power unit n in time period t. Due to the safety technical requirements of nuclear power units, the second-stage output of nuclear power units usually adopts the planned output of the day-ahead stage to avoid the impact of frequency regulation on unit performance.

[0149] 6) Pumped storage unit output and reserve adjustment constraints

[0150]

[0151] in, They are respectively the generating power and pumping power of the pumped storage unit s in the second stage during time period t.

[0152] 7) Chemical energy storage equipment output and reserve adjustment constraints

[0153]

[0154] in, They are respectively the discharge and charging power of the chemical energy storage device s in the second stage during time period t.

[0155] 8) AC tie line output and reserve adjustment constraints

[0156]

[0157] in, is the output of the second-stage AC interconnection line o in time period t.

[0158] 9) DC tie line output and reserve adjustment constraints

[0159]

[0160] in, is the output of the DC interconnection line o in the second stage during time period t.

[0161] 10) Load demand response and load shedding constraints

[0162]

[0163] in, is the load of the second stage load d in time period t; It is the demand-side reserve capacity that the second-stage load d can continue to provide after participating in demand response in period t.

[0164] The adjusted output and reserve of various resources also need to meet the operating characteristics of their own equipment. At the same time, the second stage needs to meet the system load balance constraints and branch flow constraints. The form of these constraints is exactly the same as that of the day-ahead planning stage.

[0165] 3 Model Solution

[0166] The two-stage robust optimization model proposed in this method is a min-max-min three-layer optimization problem, in which the innermost min optimization problem is a mixed integer optimization problem containing 0-1 variables. Current commercial solvers cannot directly solve the complete two-stage robust optimization model. Usually, it is necessary to use the nested column and constraint generation (NC&CG) algorithm to decompose and decouple the problem, obtain a relatively independent single-layer optimization problem, and then call the commercial solver to solve it.

[0167] The basic idea of ​​the NC&CG algorithm is to decompose the two-stage robust optimization problem into an inner-outer two-layer master-subproblem iterative form for solution. The outer master problem contains the one-stage optimization model and the two-stage variables and constraints under the worst wind power scenario found by the outer subproblem. The outer subproblem is a two-stage optimization model under the condition of fixed one-stage variables. The outer column and constraint generation algorithm iteratively solves the outer master-subproblem, in which the outer main problem transfers the optimal solution of the one-stage variables to the outer subproblem, and the outer subproblem transfers the two-stage worst wind power scenario to the outer main problem, and adds the two-stage variables and constraints under the corresponding scenario to the outer main problem. After a finite number of iterations, the optimal solution of the original max-min-max three-layer optimization problem can be finally obtained.

[0168] During the iteration process of the outer column and constraint generation algorithm, the outer main problem of each iteration can be directly solved by a commercial solver. Then the outer subproblem is a max-min two-level optimization problem, which needs to be further decomposed and solved using the inner column and constraint generation algorithm. The inner main problem contains the dual model of the two-stage optimization model under the condition of fixed one-stage variables and the two-stage dual variables and dual constraints under the conditions of the optimal two-stage 0-1 integer variables (intraday start and stop and operating conditions) found by the inner subproblem. The inner subproblem is a two-stage optimization model under the conditions of fixed one-stage variables and two-stage 0-1 integer variables. The inner column and constraint generation algorithm iteratively solves the inner main-subproblem, where the inner main problem transfers the worst wind power scenario to the inner subproblem, the inner subproblem transfers the optimal two-stage 0-1 integer variables to the inner main problem, and adds the corresponding two-stage dual variables and dual constraints to the inner main problem. After a finite number of iterations, the optimal solution of the outer max-min subproblem two-level optimization problem can be finally obtained. The flow diagram of the NC&CG algorithm is shown as follows. Figure 1 shown.

Claims

1. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve, characterized in that: The UC solution and the two-stage robust optimization model of spare capacity coordination that take into account multiple resources and equipment of source, grid, load and storage are constructed; in, is the feasible domain of the first-stage variables; x is the first-stage variables; U is the wind power uncertainty set; w is the uncertainty variable of the actual available wind power; is the feasible domain of the second-stage variables after the first-stage variables x and the actual available wind power w are given; y and z are the second-stage continuous variables and 0-1 integer variables respectively; c, d, g, A, b, E, G, f, R, D, T, and v are the constant matrices of the objective function and constraints respectively.

2. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The objective function of the first stage is to minimize the sum of the operation and standby costs of various resources and equipment under the scenario of wind power available power predicted on the day before; Among them, N G is the total number of thermal power units; are the operating cost, startup cost, minimum technical output cost, and reserved standby cost of thermal power unit g, respectively. The unit operating cost is a piecewise linear function related to the output range of each unit and the corresponding energy price; p g,t ,y g,t 、x g,t , are the output, startup status, operation status, positive reserve capacity, and negative reserve capacity of thermal power unit g in period t; N H is the total number of hydropower units; Reserved standby cost for hydropower unit h; are the positive and negative reserve capacities of hydropower unit h in time period t, respectively; is the total number of pumped storage units; Reserved reserve costs for pumped storage units; are the positive and negative reserve capacities of pumped storage unit s in time period t, respectively; is the total number of chemical energy storage devices; Reserved reserve costs for chemical energy storage equipments; are the positive and negative reserve capacities of chemical energy storage device s in time period t, respectively; is the total number of communication lines; Reserved standby fee for the AC line o; are respectively the positive and negative reserve capacities of the AC tie line o in time period t; is the total number of DC tie lines; Reserved reserve cost for DC tie line o; are respectively the positive and negative reserve capacities of DC tie line o in period t; N D is the total number of load nodes; is the reserve cost for load d; r d,t is the reserve capacity of load d participating in demand-side response in period t.

3. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The system power balance constraints in the first stage are: Among them, p h,t is the output of hydropower unit h in period t; p r,t is the output of wind turbine r in period t; are respectively the power generation and pumping power of pumped storage unit s in time period t; are the discharge and charge powers of chemical energy storage device s in time period t, respectively; is the transmission power of the AC tie line o in time period t; is the transmission power of DC tie line o in time period t; p d,t is the load demand of load d in time period t.

4. A two-stage robust unit commitment method considering collaborative optimization of multiple types of power reserve according to claim 1, characterized in that: The constraints of the thermal power units in the first phase are: Among them, z g,t is the shutdown state of thermal power unit g in period t; TU g , TD g are the minimum continuous start and stop time of thermal power unit g respectively; are the maximum and minimum technical outputs of thermal power unit g respectively; ΔT is the duration of a single dispatch period; They are the up and down climbing rates of thermal power unit g respectively.

5. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The constraints of the hydropower units in the first phase are: Among them, x h,t is the operating status of hydropower unit h in time period t; are the maximum and minimum technical outputs of hydropower unit h, respectively; H(j) is the set of hydropower units h equipped in reservoir j; η h is the water-to-electricity conversion efficiency of the hydropower unit; ρ is the density of water; g is the acceleration of gravity; h j is the net head height of reservoir j. The change of net head height is usually small and can be assumed to be a fixed value; is the power generation flow of hydropower unit h in time period t; are the maximum and minimum power generation flow of hydropower unit h respectively; is the outflow (discharge) flow of reservoir j in period t; is the water discharge of reservoir j in period t; are the maximum and minimum outflows of reservoir j respectively; are the maximum and minimum water discharge of reservoir j respectively; I(j) is the set of upstream reservoirs i of reservoir j; vj ,t is the storage capacity of reservoir j in time period t; is the predicted natural water flow of reservoir j in period t; α i is the water loss rate from reservoir i to reservoir j; τ i is the time lag of water flow from reservoir i to reservoir j; are the maximum and minimum storage capacities of reservoir j respectively.

6. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: Wind turbine constraints in the first phase: In the formula, is the predicted available power of wind farm r in period t; 6) Nuclear power plant constraints in, are the state variables of the A operation mode and G operation mode of the nuclear power unit n, respectively. In the A mode, the nuclear power unit does not participate in the peak load regulation and maintains the rated power operation. In the G mode, the nuclear power unit participates in the peak load regulation and adopts a specific daily load tracking mode. n,t is the output of nuclear power unit n in time period t; is the rated power of nuclear power unit n; is the daily load following mode output curve adopted by nuclear power unit n; The constraints of the pumped storage units in the first stage are: in, are the power generation and pumping state variables of pumped storage unit s in time period t, respectively; are the maximum and minimum technical outputs of pumped storage unit s under power generation conditions; are the pumping power of the pumped storage unit s respectively. When the pump turbine is in the pumping state, its guide vane is fixed at the optimal opening, and the active power absorbed from the system is generally the rated value; is the virtual power generation of pumped storage unit s in time period t, which is positive under power generation conditions and negative under pumping conditions; are the water-to-electricity conversion coefficients of the pumped storage unit s under power generation and pumping conditions respectively; are the power generation flow and pumping flow of pumped storage unit s in time period t respectively; are the maximum and minimum limits of power generation flow of pumped storage unit s, respectively; is the rated value of pumped storage unit s’ pumping flow; S(j) is the set of pumped storage units s equipped in reservoir j; is the outflow of reservoir j in period t; v j,t is the remaining storage capacity of reservoir j in period t; are the maximum and minimum remaining capacities allowed for reservoir j during the scheduling process.

7. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The constraints of the chemical energy storage equipment in the first phase are: in, are the discharging and charging operating states of the chemical energy storage device s in time period t, respectively; are the maximum discharge and charge powers of chemical energy storage device s, respectively; is the virtual power generation of the chemical energy storage device s in time period t, which is positive under discharge conditions and negative under charge conditions; is the charge and discharge efficiency of chemical energy storage device s; is the remaining capacity of the chemical energy storage device s in time period t; are the maximum and minimum remaining capacities allowed for chemical energy storage equipment s in the scheduling process; The AC tie line constraints of the first phase are: in, are the positive and reverse power flow transmission limits of the AC tie line o respectively; is the planned transmission power value of the AC interconnection line o in time period t obtained by decomposition according to the long-term contract; The DC tie line constraints of the first stage are: Among them, x o,t is the operating state of the DC tie line o in time period t; The forward and reverse power flow transmission limits of the DC tie line o respectively; are the power rise and fall rate limits of tie line o respectively; They are the forward and reverse adjustment states of tie line o in time period t respectively; are auxiliary variables respectively; is the planned transmission power value of the DC tie line o in time period t obtained by decomposing it according to the long-term contract; The load demand response constraints of the first stage are: In the formula, is the predicted load demand of load d in period t; is the maximum value of the demand-side response reserve of load d in period t; The branch flow constraints in the first stage are: Where P l max , P l min are the forward and reverse power flow transmission limits of branch l respectively; F g-l 、F h-l 、F r-l , F d-l They are the power flow transfer distribution factors of the thermal power unit g, hydropower unit h, wind power unit r, pumped storage unit s, chemical energy storage equipment s, the end point on one side of the AC interconnection line o, the end point on one side of the DC interconnection line o, and the node where the load d is located to the line l.

8. The two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1 is characterized in that: The objective function of the second stage: The second stage is a two-layer optimization problem. The inner problem objective is to minimize the sum of the cost of calling multiple resource reserves, the penalty cost of wind abandonment and the penalty cost of load shedding under a given wind power available power scenario. The specific objective function is: Among them, the superscript ^ indicates the second-stage variables; The cost of calling up the thermal power unit g for standby; is the positive and negative reserve capacity of thermal power unit g called in time period t; Costs for calling up the hydropower unit g for standby; are respectively the positive and negative reserve capacity of hydropower unit h called in time period t; Costs for calling pumped storage units for standby; are respectively the positive and negative reserve capacity of the pumped storage unit s called in time period t; Costs for calling chemical energy storage equipment for standby; are respectively the positive and negative reserve capacity of chemical energy storage device s called in time period t; Costs for calling up the AC line for standby; are respectively the positive and negative reserve capacity of the AC tie line o called in time period t; Costs for calling up the DC interconnection line for backup; are respectively the positive and negative reserve capacity of DC tie line o called in time period t; The cost of calling up the load reserve; is the reserve capacity called for load d; is the penalty fee for wind turbine r’s wind abandonment; is the wind abandonment volume of wind turbine r in period t; is the load shedding penalty cost of load d; is the load shedding amount of load d in time period t; The output and reserve adjustment constraints of thermal power units in the second phase are: in, is the output of the thermal power unit g in the second stage during period t; The output and reserve adjustment constraints of the hydropower units in the second phase are as follows: in, is the output of hydropower unit h in period t in the second stage.

9. A two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The wind turbine abandonment constraints in the second phase are: in, is the output of wind turbine r in the second stage during period t; w r,t is the actual available power of wind farm r in the second stage during period t, w r,t The uncertainty of is described by the uncertainty set U; The output adjustment constraints of nuclear power in the second phase are: in, is the output of the second-stage nuclear power unit n in time period t; due to the safety technical requirements of nuclear power units, the second-stage output of nuclear power units usually adopts the day-ahead planned output to avoid the impact of frequency regulation on unit performance; The output and reserve adjustment constraints of the pumped storage units in the second stage are: in, They are respectively the generating power and pumping power of the pumped storage unit s in the second stage during time period t.

10. The two-stage robust unit commitment method considering coordinated optimization of multiple types of power reserve according to claim 1, characterized in that: The output and reserve adjustment constraints of the chemical energy storage equipment in the second phase are: in, are the discharge and charge powers of the chemical energy storage device s in the second stage in time period t, respectively; The AC tie line output and reserve adjustment constraints in the second phase are: in, is the output of the second-stage AC contact line o in time period t; The DC tie line output and reserve adjustment constraints in the second phase are: in, is the output of the DC tie line o in the second stage during time period t; The load demand response and load shedding constraints in the second stage: in, is the load of the second stage load d in time period t; It is the demand-side reserve capacity that the second-stage load d can continue to provide after participating in demand response in period t.

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