WO2020088206A1 - 权重与约束关联调整的电网实时发电控制优化决策方法 - Google Patents

权重与约束关联调整的电网实时发电控制优化决策方法 Download PDF

Info

Publication number
WO2020088206A1
WO2020088206A1 PCT/CN2019/110363 CN2019110363W WO2020088206A1 WO 2020088206 A1 WO2020088206 A1 WO 2020088206A1 CN 2019110363 W CN2019110363 W CN 2019110363W WO 2020088206 A1 WO2020088206 A1 WO 2020088206A1
Authority
WO
WIPO (PCT)
Prior art keywords
power
grid
active
power plant
time
Prior art date
Application number
PCT/CN2019/110363
Other languages
English (en)
French (fr)
Inventor
徐泰山
汪马翔
范越
王昊昊
常康
董凌
张昊天
李吉晨
李延和
Original Assignee
国电南瑞科技股份有限公司
国网青海省电力公司
南瑞集团有限公司
国家电网有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 国电南瑞科技股份有限公司, 国网青海省电力公司, 南瑞集团有限公司, 国家电网有限公司 filed Critical 国电南瑞科技股份有限公司
Publication of WO2020088206A1 publication Critical patent/WO2020088206A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Definitions

  • the invention relates to power grid dispatching operation in the field of control technology, in particular to a method for real-time power generation control optimization decision-making in which the weights and constraints are adjusted in association.
  • Wind and solar new energy power generation has the characteristics of gaps and randomness. As the proportion of new energy power generation continues to increase, the random fluctuation of grid-connected power on the power generation side of the grid increases, and the load itself has fluctuations. After the power grid, the load volatility increases. In order to ensure that the frequency fluctuation of the power grid remains within the allowable range, it is necessary to control the grid-connected power of the power plant in real time. Due to differences in power generation economic and environmental performance, ultra-short-term power generation capacity prediction performance and grid-connected power regulation performance in response to dispatch control commands of different power plants, changes in grid-connected power of different power plants also have differences in power grid security and stability. In addition, real-time power generation control in the power market environment also needs to consider the implementation of spot trading power.
  • Patent ZL 201310174543.0 New energy grid-connected power control method based on predictive adjustment performance and safety constraints for the scenario where the regulation center determines the new energy field station control group and the output adjustment direction and amount of each new energy field station control group, According to the control performance cost ratio index of the new energy power station's grid-connected power control on the change of the grid security and stability margin at the current moment, the new energy power station in the new energy field station control group is divided into multiple power plant groups with similar control performance cost ratio indexes.
  • priority is given to increasing the power of the new energy field station control group with a smaller control performance cost than the index, and priority is given to increasing the predicted performance index and the adjustment performance index within the power station group
  • the sum of the power of the large power station when the control center requires the output of the new energy field station control group to be reduced, priority is given to reducing the power of the power station group in the new energy field station control group whose control performance cost is greater than the index, and priority is given to the power station group Reduce the active power of power plants with large regulation performance indexes.
  • This patent takes into account the characteristics of the impact of new energy output on the safety and stability of the power grid and its output prediction performance and regulation performance in the control of new energy power generation, but the applicable scenarios are relatively limited, and the control center needs to determine the new energy field station control group and each new energy. The output adjustment direction and adjustment amount of the station control group.
  • the patent "Real-time Active Power Control Method for Grid-connected Power Plants Considering the Electricity Trading Plan” proposes to use the ratio of the power plant electricity transaction completion rate to the transaction plan execution progress as its electricity transaction execution rate index, establishing a comprehensive A real-time power generation control model that considers the economic and environmental performance of power plants, predicted performance, regulation performance, and power transaction execution rate.
  • the purpose of the present invention is to propose a method for optimizing decision-making for real-time power generation control of power grids in which the weights and constraints are adjusted.
  • comprehensive consideration is given to the characteristics of power plant output impact on power grid security and stability, as well as economic and environmental performance of power plants Performance, adjustment performance and spot transaction execution status, etc., by setting weights, and adjusting the output weights of the relevant power plants under the condition that the transmission equipment / section power is not limited, the weights are related to the constraints, ensuring that the power generation control of the grid meets real-time, Safety and economic environmental requirements.
  • the technical scheme adopted by the present invention is: a method for optimizing decision-making of real-time power generation control of power grids in which the weights and constraints are adjusted, including:
  • S1 Obtain the current grid operation status data, the active power injected into the grid by each node in the internal network, the sensitivity of the active power transmission equipment and stable section active power of the current control center, and the power plant collection, load collection, DC system AC in the internal network Side node set and internal and external network tie line set;
  • the power transmission equipment / section with the active power reaching the limit corresponding to the S6 optimization solution result is recorded as the restricted equipment / section, and the other power transmission equipment / section is recorded as the unrestricted equipment / section;
  • the real-time control optimization decision-making comprehensive index is selected as the comprehensive index without considering the safety performance of the power grid;
  • the grid-connected active command value finally obtained by each equivalent power plant is used as the grid-connected active command value of its next real-time control cycle, and the corresponding power plants are calculated according to the grid-connected active command value of each equivalent power plant The grid-connected active command value of the next real-time control cycle.
  • S1 includes:
  • S102 acquires the current time t 0 comprises the operating state of the power grid external network data to the present time t 0 control center SCADA system state estimation network application function operating condition is given as a reference to the control center on a hair
  • the latest operation status of the power grid is optimized and adjusted, and the integrated operation status of the power grid including the internal and external networks is generated and recorded as S 0.
  • S 0 Based on S 0 , each power plant, load, AC system AC side and internal network in the internal network are calculated.
  • the active power injected into the power grid of external contact nodes The sensitivity of the active power transmission equipment and stable section active power of the current control center; record the power plant set in the internal network as A, the load set as L, the DC side AC side node set DC and the internal and external network Contact line collection TL;
  • S103 Obtain the current grid operating status data of the intranet at t 0 and record it as S 0. Based on S 0, calculate the active power injected into the grid by each power plant, load, and AC side of the DC system.
  • the power transmission responsible for overload monitoring of the current control center Equipment and stable section active power sensitivity note that the power plant set in the internal network is A, the load set is L, the DC side AC side node set DC and the internal and external network tie line set TL, and the TL is the empty set.
  • the set of power plants that generate electricity according to the dispatch plan in set A is defined as B
  • the set of power plants controlled by the current control center in real time is C
  • the set of power plants controlled by other control centers in real time is D
  • C The comprehensive indicators of real-time control optimization decision of each power plant are:
  • ⁇ i is the comprehensive index of real-time control optimization decision of power plant i in C
  • ⁇ si , ⁇ ei , ⁇ pi and ⁇ ci are the safety and stability performance index of power plant i obtained by the analysis of the current dispatch center automation system.
  • W i, W i.0, t si and t ei spot trading scheme are scheduling automation power system analysis i get the power plant for the current control center , Completed spot transaction electricity, spot transaction plan start time and spot transaction plan end time;
  • k s , k e , k p , k c and k t are the corresponding safety and stability performance indicators, economic and environmental performance indicators, ultra short-term
  • ⁇ si , ⁇ ei , ⁇ pi and ⁇ ci are obtained by the control center dispatch automation system through online security and stability analysis application functions, power transaction application functions, and power plant operation monitoring and management application function analysis; W i , W i.0 , t si and t ei are obtained from the power management application function analysis of the current control center dispatch automation system.
  • the above functional applications can use the existing functional applications of the control center dispatch automation system.
  • the indexes ⁇ si , ⁇ ei , ⁇ pi and ⁇ ci are all greater than 0. The larger the value, the better the corresponding performance.
  • the ratio of the absolute value of the active deviation of each link in the TL to the transmission capacity is less than the set value ⁇ p and reactive power
  • the ratio of the absolute value of the deviation to the transmission capacity is less than the set value ⁇ q as a constraint, integrate the internal and external network grid operation status, for the case of no feasible solution, by gradually increasing ⁇ p , ⁇ q until the Optimize the solution.
  • the formula for grouping the power plants to be controlled is as follows:
  • SL-oriented control center responsible for collection of airborne surveillance power transmission and stable cross section consisting of, S il, S jl respectively S 0 under C in plant i, j grid active the SL overload monitored transmission equipment / stabilizing section l Active sensitivity
  • a is the preset threshold difference of real-time control optimization decision-making comprehensive index between different power plants
  • b is the preset active sensitivity of grid-connected active power to overload monitoring of transmission equipment or stable section between different power plants Threshold of difference;
  • each group of generators after grouping Take each group of generators after grouping as a set, and record the grouping sequence of power plants to be controlled as C 1 , C 2 , ..., C n , where n is the number of groups.
  • the number of power plants in each group can be greater than or equal to 1.
  • S4 the use of equivalent power plants G 1, G 2, ..., G n equivalently C 1, C 2, ..., C n in each group of plants; S each at the 0
  • the sum of the grid-connected active power plants in the group is regarded as the corresponding grid-connected active power of equivalent power plants; the average value of the comprehensive indicators of the real-time control optimization decisions of the power plants in each group is taken as the synthesis of the real-time control optimization decisions of the corresponding equivalent power plants
  • Indicators For the transmission equipment and stable section of each overload monitoring in SL, the average of the grid-connected active power of the power plants in each group to the active sensitivity of the transmission equipment and stable section of the overload monitoring in SL is taken as the corresponding equivalent power plant and The active sensitivity of the network active power to the same transmission equipment and stable section of the overload monitoring in SL.
  • the real-time power generation control period is set to T, taking into account the grid-connected active power regulation speed of the power plant, and the upper limit P k.1.u and the lower limit of the grid-connected active power of each equivalent power plant G k at t0 + T P k.1.d is:
  • P kimax and P kimin plants were equivalent group G k C k corresponding to the plant in the plant i in time t 0 + T grid active upper and lower limits;
  • P ki0 S 0 is the power of C k
  • the grid-connected active power of plant i, v ki0 is the grid-connected active power regulation speed of power plant i in C k under S 0 ;
  • T r the thermal standby time limit of the power plant
  • P k.1.us and lower limit P k.1.ds of each equivalent power plant G k can be used for thermal standby at time t 0 + T as:
  • P ' kimax and P' kimin are equivalent to the upper and lower grid-connected active power limit of power plant i in power plant C k at t 0 + T + T r respectively ;
  • the power plant i in the set B / D can be used for the hot-standby grid-connected active upper limit P i1.1.us / P i2.1.us and the lower limit P i1.1.ds / P i2 at time t 0 + T. 1.ds is:
  • P i1.1.max / P i2.1.max and P i1.1.min / P i2.1.min are the power plant i1 / i2 in the set B / D at time t 0 + T + T r
  • the upper and lower limits of grid-connected active power; P i1.1 / P i2.1 is t 0 + the grid-connected active power plan value of the power plant i1 / i2 in the B / D set at time T v i1.1 / v i2.1 is t
  • the pre-established linear programming model is:
  • the grid-connected active power command value of the equivalent power plant G k calculated at time t 0 + T calculated by S6 is substituted into the overload monitoring power transmission equipment / stable section active power constraint equation in formula (6), and SL
  • the set of the combination of power transmission equipment and stable section with active power reaching the limit is denoted as SL1
  • the set of combination of power transmission equipment and stable section with active power not reaching the limit is denoted as SL2.
  • the set of power plants corresponding to all equivalent power plants in E is recorded as EG, then the real-time control optimization decision of each power plant in EG is synthesized.
  • the indicators are:
  • the average value of the real-time control optimization decision-making comprehensive index of the power plant corresponding to each equivalent power plant in E is taken as the corresponding real-time control optimization decision-making comprehensive index of the equivalent power plant.
  • the optimal solution range is replaced by G to E, and the range of equipment / section active power limit constraints is adjusted from SL to SL2, then the specific representation of the linear programming model is adjusted to:
  • P ki0 is the initial value
  • P kimin is t 0 + T at the time of the lower limit of the grid-connected active power command
  • the total amount is allocated to the equivalent power plant G k
  • the power plants of the power plant get the grid-connected active power command value at time t 0 + T of each power plant.
  • the grid-connected active power under each power plant S 0 corresponding to the equivalent power plant G k is taken as its grid-connected active command value at time t 0 + T.
  • the present invention has the following advantages and advancements:
  • the power plant output is optimized Whether the weight and the constraint reach the boundary, to meet the actual demand of optimizing the weight of the power plant's economic and environmental performance, predictive performance, regulatory performance and spot transaction execution under unconstrained grid security;
  • FIG. 1 is a schematic flowchart of a method embodiment of the present invention.
  • Some of the existing power grid real-time power generation control optimization decision-making methods consider the economic and environmental performance of the power plant, the predicted performance (new energy power generation), the adjustment performance in response to the control instructions, and the power transaction execution rate indicators, and the product of these indicators is used as the power generation
  • the weight of the plant output optimization takes into account the power balance, transmission equipment / section limit and peak shaving constraints, and takes into account the active power sensitivity of the power plant output to the transmission equipment / section, which is solved by a mathematical programming algorithm, but does not consider the frequency modulation constraints.
  • the frequency regulation constraint is added to the constraints, it is only through simple The arithmetic to calculate the output of the power plant is only suitable for simple radiant power grids.
  • the present invention proposes to comprehensively consider the characteristics of the power plant output on the safety and stability of the power grid and its economic and environmental performance, predictive performance, regulatory performance and spot transaction execution.
  • linear weighting of various indicators it is used as a comprehensive index for power plant output optimization.
  • the weighting coefficients of the indicators can be flexibly set by the control center according to the importance of different influencing factors, taking into account constraints such as real-time active power adjustable space and speed of the power plant, power transmission equipment limits, stable section forward and reverse limits, frequency modulation and peak regulation, etc.
  • a method for optimizing decision-making for real-time power generation control of a power grid according to the present invention includes the following steps:
  • S1 Obtain the current grid operation status data, the active power injected into the grid by each node in the internal network, the sensitivity of the active power transmission equipment and stable section active power of the current control center, and the power plant collection, load collection, DC system AC in the internal network Side node set and internal and external network tie line set;
  • the power transmission equipment / section with the active power reaching the limit corresponding to the S6 optimization solution result is recorded as the restricted equipment / section, and the other power transmission equipment / section is recorded as the unrestricted equipment / section;
  • the real-time control optimization decision-making comprehensive index is selected as the comprehensive index without considering the safety performance of the power grid;
  • the grid-connected active command value finally obtained by each equivalent power plant is used as the grid-connected active command value of its next real-time control cycle, and the corresponding power plants are calculated according to the grid-connected active command value of each equivalent power plant The grid-connected active command value of the next real-time control cycle.
  • step S1 the current operating time of the power grid is set to t 0. If the control center has a higher-level control center, the operation status of the intranet given by the control system's dispatch automation system state estimation application function at time t 0 As a benchmark, the latest operation status of the power grid issued by the higher-level control center is optimized and adjusted, and the integrated operation status of the power grid including the internal and external networks is generated and recorded as S 0 , and each of the internal networks is calculated based on S 0 Active power injected into the power grid by the power plant, load, AC side nodes of the DC system, and external connection nodes of the internal network
  • the medium load set is denoted as L
  • the set of nodes on the AC side of the DC system in the internal network is denoted as DC
  • the set of internal and external network tie lines is denoted as TL;
  • the control center does not have a higher-level control center, then based on the grid operation state given by the control system's dispatch automation system state estimation application function at time t 0 , the power plant, load, and the AC side nodes of the DC system injected into the grid are calculated.
  • the active power is sensitive to the power transmission equipment and the stable section active power of the control center responsible for overload monitoring.
  • the operation state of the power grid given by the state automation application system of the control center at time t 0 is recorded as S 0
  • the collection of power plants in the power grid is A, record the load set in the grid as L, record the set of nodes on the AC side of the DC system in the grid as DC, and set the set of internal and external tie lines TL as the empty set;
  • the specific method of integrating the internal and external network operating status is: first, based on the internal network operating status given by the control center dispatch automation system status estimation application function at time t 0 , by adjusting the latest Grid-connected active power, reactive power, and load active and reactive power of the power plant in the power grid operation state, and sum of squared active power adjustment square sums of power plants in the external grid, sum of square reactive power adjustment power squares, and load active power squared square sum And the minimum sum of the sum of the square of the load reactive power adjustment is the optimization goal.
  • the ratio of the absolute value of the active deviation of each tie line in TL and its transmission capacity are less than the set value ⁇ p and the ratio of the absolute value of the reactive deviation and its transmission capacity.
  • ⁇ p can be 0.01
  • ⁇ q can be 0.02
  • Step S2 let A be the set of power plants that generate electricity according to the dispatch plan as B, A as the set of power plants controlled by this control center in real time as C, and A as the set of power plants controlled by other control centers in real time as D, A be B, The union of C and D, through formula (1) to calculate the real-time control optimization decision comprehensive index of each power plant in C;
  • ⁇ i is the comprehensive index of real-time control optimization decision of power plant i in C
  • ⁇ si is the safety and stability performance index of power plant i in C newly given by the online safety and stability analysis application function of the dispatching automation system of the control center.
  • the index is greater than 0, and the larger the value, the greater the power plant's grid-connected active power increase. The better the security and stability of the power grid.
  • ⁇ ei is the latest economic and environmental performance index of the power plant i in C given by the control center dispatch automation system power transaction application function. , The index is greater than 0, the greater the value, the better the economic and environmental performance of the power plant.
  • ⁇ pi is the ultra-short-term power generation capacity of the power plant i in C, which is newly given by the control center dispatching automation system power plant operation monitoring and management application function.
  • Predicted performance index the index is greater than 0, the greater the value, the higher the accuracy of the power plant ’s ultra-short-term power generation capacity prediction
  • ⁇ ci is the latest given C-zhong power plant for the control and monitoring center dispatch automation system power plant operation monitoring and management application function i Active power regulation performance index that responds to the active command of the control center. This index is greater than 0. A larger value indicates that the power plant responds to the regulation.
  • W i, W i.0, t si, t ei are central dispatching electricity spot trading scheme
  • Step S3 to satisfy formula (2) as a judgment condition for power plant grouping, group power plants in C, and for power plants in C that cannot be grouped with other power plants in the same group, separate each power plant separately
  • One power plant is regarded as one group, and each group of power plants after grouping is regarded as a set, denoted as C1, C2, ..., Cn, n is the number of groups;
  • SL-oriented control center responsible for the overload monitoring power transmission and stable cross section composed of a set, S il, S jl respectively S 0 under C in plant i, j grid active power transmission device or the stability of the SL overload monitoring Section 1 active sensitivity
  • a and b are the difference threshold between the set comprehensive indicators of the power plant real-time control optimization decision and the difference threshold between the power plant's grid-connected active power for overload monitoring of the transmission equipment and the stable section active sensitivity Value; where, the larger the value of a and b, the shorter the time of optimization decision, the lower the accuracy, otherwise, the longer the time of optimization decision, the higher the accuracy, comprehensively weigh the time and accuracy of optimization decision, a usually takes the value It is 0.05 and b is usually 0.03.
  • step S4 equivalent power plants G1, G2, ..., Gn are used to replace the power plants in C1, C2, ..., Cn respectively, the set of equivalent power plants is denoted as G, and C1, C2, ...,
  • the sum of the grid-connected active power of the power plant in Cn is the grid-connected active power of the corresponding equivalent power plant under S0, and the average value of the comprehensive index of the real-time control optimization decision of the power plant in C1, C2, ..., and Cn is taken as the corresponding Value-added power plant real-time control optimization decision-making comprehensive index, for each overload monitoring transmission equipment and stable section in SL, the grid-connected active power of the power plant in C1, C2, ..., Cn is respectively used to stabilize the overload monitoring transmission equipment in SL
  • the average value of the active power sensitivity of the cross-section is taken as the corresponding equivalent power plant grid-connected active power to the same power transmission equipment in SL with overload monitoring, and the active power sensitivity of the stable cross-section;
  • Step S5 Set the real-time power generation control period to T, taking into account the grid-connected active power regulation speed of the power plant, calculate the upper and lower limits of the grid-connected active power of each equivalent power plant at time t 0 + T through formula (3), and set the power plant
  • the hot standby time limit is T r
  • the upper and lower limits of the grid-connected active power that can be used for hot standby by each equivalent power plant at time t 0 + T are calculated by formula (4)
  • the power plants in B and D are calculated by formula (5).
  • t 0 + T moment can be used for hot standby grid-connected active power upper and lower limits;
  • P k.1.u and P k.1.d are the upper limit and lower limit of the grid-connected active power of the equivalent power plant G k at t 0 + T
  • P kimax and P kimin are the equivalent power plant G, respectively.
  • the upper and lower bound of grid-connected active power of power plant i in k at time t 0 + T, P ki0 is the equivalent power plant under S0, and the power of grid-connected power plant i in k , v ki0 is the equivalent power plant G at t 0 k 's grid-connected active power regulation speed of power plant i, P ' kimax and P' kimin are equal to the power plant G k 's upper and lower grid-connected active power upper limit and lower limit at time t 0 + T + T r , P k.
  • 1.us and P k.1.ds are the grid-connected active power upper and lower limits of the equivalent power plant G k that can be used for hot standby at t 0 + T
  • P i1.1.max and P i1.1.min are respectively Upper limit and lower limit of grid-connected active power of power plant i1 in B at time t 0 + T + T r
  • P i1.1 is the grid-connected active power plan value of power plant i1 in B at time t 0 + T
  • v i1.1 is t
  • the grid-connected active power regulation speed of power plant i1 at time 0 , P i1.1.us and P i1.1.ds are t 0 + T at time B, respectively, and the grid-connected active power upper limit of power plant i1 available for thermal backup at time B the lower limit, P i2.1.max, P i2.1.min D, respectively, in the plant i2 t 0 + T + T r the time the upper and lower grid-active P i2.1
  • Step S6 Calculate the grid-connected active power command value of each equivalent power plant at time T 0 + T by solving the optimization function represented by formula (6);
  • ⁇ ck optimized for real-time control decisions equivalent plant comprehensive index k P k.1 is equivalent in time t 0 + T G k grid plant active command value, P i3.1 to t 0 + The active power plan value of the tie line i3 injected into the intranet at time T TL, P i4.1 is the predicted value of the active power of load i4 at time t 0 + L at time T, and ⁇ is the net loss coefficient of the intranet at time t 0 , f 0 and K f is the frequency and active static frequency characteristic coefficients of the internal network at time t 0 , fr is the rated frequency of the internal network, ⁇ f is the set allowable deviation of the internal network frequency, for overload monitoring transmission equipment in SL , P sl .l.lmt.FD and P sl.l.lmt.OD are equal, which is taken as the active overload limit of the transmission device l calculated by the power factor of the transmission device l unchanged at t 0
  • P k.0 is S 0 Equivalent Plant active grid G k
  • S Bli1 B is S 0 at the grid active plant i1 active sensitivity overload monitoring device or stabilizing transmission section of l
  • P i1.0 B is in the S 0 plants of i1 active grid
  • DLI 2 S as S 0 D in the active grid active plant i2 sensitivity overload monitoring device or stabilizing transmission section of l
  • P i2.0 0 D is S in the plant i2 active grid
  • S Lli4 is the active power sensitivity of the load i4 in L under S 0 to the active power of the overload monitoring transmission equipment or stable section l
  • P i4.0 is the active power of the load i4 in L under S
  • ⁇ f usually takes a value of 0.02 Hz.
  • Step S7 Substitute the grid-connected active power command value of each equivalent power plant at time t 0 + T calculated in step 6 into the power transmission equipment for overload monitoring and stable cross-section active power constraint equation in formula (6), and achieve active power in SL
  • the set of power transmission equipment and stable cross-section combinations with limit values is denoted as SL1
  • the set of power transmission equipment and stable cross-section combinations with active power that does not reach the limit is denoted as SL2;
  • step S8 the set of equivalent power plant combinations where the absolute values of the active sensitivities of the power transmission equipment or stable sections under SL at S0 in G are less than the set value ⁇ s is recorded as E, and the value of ⁇ s may be 0.05.
  • Step S9 if E is not empty, record the set of power plants corresponding to all equivalent power plants in E as EG, calculate the comprehensive index of real-time control optimization decision of each power plant in EG by formula (7), and separate E The average value of the real-time control optimization decision-making comprehensive index of the power plant corresponding to each equivalent power plant in the corresponding equivalent power plant real-time control optimization decision-making comprehensive index, otherwise, go to step 11;
  • Step S10 by solving the optimization function represented by formula (8), the grid-connected active power command value of each equivalent power plant at time t 0 + T is calculated, which is used to update the E-medium power plant calculated in step S6.
  • Step S11 the respective G for equivalent plants, if P k.1 greater than P k.0 and (P k.1 -P k.0) / P k.1 than the set value [epsilon], places (P k .1 -P k.0 ) is the total amount,
  • P ki0 is the initial value
  • P kimax is t 0 + T
  • the upper limit of the grid-connected active power command the total amount is allocated to the equivalent power plant G k
  • Corresponding power plants get the grid-connected active power command value of each power plant at time t 0 + T;
  • P ki0 is the initial value
  • P kimin is t 0 + T at the time of the lower limit of the grid-connected active power command
  • the total amount is allocated to the equivalent power plant G k
  • the power plants of the power plant get the grid-connected active power command value at time t 0 + T of each power plant.
  • ⁇ is usually 0.01;
  • the grid-connected active power under each power plant S 0 corresponding to the equivalent power plant G k is taken as its grid-connected active command value at time t 0 + T.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.
  • computer usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processing machine, or other programmable data processing device to produce a machine that enables the generation of instructions executed by the processor of the computer or other programmable data processing device
  • These computer program instructions may also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, the instructions The device implements the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and / or block diagrams.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operating steps are performed on the computer or other programmable device to produce computer-implemented processing, which is executed on the computer or other programmable device
  • the instructions provide steps for implementing the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and / or block diagrams.

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

一种权重与约束关联调整的电网实时发电控制优化决策方法，通过求解以反映发电厂出力对电网安全稳定影响特性及其经济环保性能、预测性能、调节性能和现货交易执行情况的综合指标为权重的发电控制优化决策模型，根据输电设备/断面是否达到限额，将输电设备/断面划分为受限类和不受限类；针对与受限设备/断面的有功灵敏度较小的发电厂，采用不考虑其电网安全性能的综合指标为权重，并只计及不受限类设备/断面的过载约束进行发电控制优化决策，实现了权重与约束关联的自适应调整，保障电网发电控制满足实时性、安全性和经济环保要求。

Description

权重与约束关联调整的电网实时发电控制优化决策方法 技术领域
本发明涉及电网调度运行于控制技术领域，特别是一种权重与约束关联调整的电网实时发电控制优化决策方法。
背景技术
风光新能源发电具有间隙性和随机性特点，随着新能源发电占比不断提高，电网中发电侧并网功率随机波动性增大，负荷自身就具有波动性，分布式新能源发电接入配电网后导致负荷波动性增大，为了保障电网频率波动幅度保持在允许范围内，就需要对发电厂的并网功率进行实时控制。由于不同发电厂的发电经济环保性能、超短期发电能力预测性能和响应调度控制指令的并网功率调节性能存在差异，不同发电厂的并网功率变化对电网的安全稳定性能影响也存在差异。此外，在电力市场环境下实时发电控制还要考虑现货交易电量的执行情况。
为了能够在电力市场环境下满足电网安全可靠、经济环保运行要求下抑制电网频率波动，将电网频率偏差控制在允许范围内，就需要建立反映发电厂出力对电网安全稳定影响特性及其经济环保性能、出力预测性能、调节性能和现货交易执行情况，计及发电厂出力调节速度的可调空间约束、电网安全稳定运行约束和电网运行备用约束的优化决策模型，并能够快速求解，满足控制的实时性要求。
专利ZL 201310174543.0“基于预测调节性能和安全约束的新能源并网功率控制方法”，针对调控中心确定新能源场站控制组及每个新能源场站控制组的出力调整方向和调整量的场景，提出根据当前时刻新能源电站并网功率控制对电网安全稳定裕度变化的控制性能代价比指标，将新能源场站控制组中的新能源电站分成多个控制性能代价比指标相近的电站群。在调控中心要求新能源场站控制组的出力增加时，优先增加该新能源场站控制组中控制性能代价比指标小的电站群有功，在电站群内优先增加预测性能指标和调节性能指标两者之和大的电站的有功；在调控中心要求新能源场站控制组的出力降低时，优先降低该新能源场站控制组中控制性能代价比指标大的电站群有功，在电站群内优先降低调节性能指标大的电站的有功。该专利在新能源发电控制中考虑了新能源出力对电网安全稳定影响特性及其出力预测性能和调节性能，但是适用的场景比较局限，需要调控中心确定新能源场站控制组及每个新能源场站控制组的出力调整方向和调整量。专利“计及电量交易计划的发电厂并网有功功率实时控制方法”(受理号：201610627240.3)提出将发电厂电量交易完成率与交易计划执行进度 之比作为其电量交易执行率指标，建立了综合考虑发电厂经济环保性能、预测性能、调节性能和电量交易执行率的实时发电控制模型。对于发电厂出力的电网安全稳定影响特性，只是以发电厂出力对输电设备/稳定断面功率的灵敏度在输电设备/稳定断面功率约束方程中有所体现，还不能全面反映发电厂出力对电网各类安全稳定的影响特性。在功率平衡方程中没有考虑调频的要求，在输电断面安全稳定限额约束中没有考虑反向限额的约束要求，也没有根据优化解下约束条件达到边界的具体情况，对发电厂出力的权重进行调整后，对相关电厂出力进行重新优化的计算策略。此外，该专利也不能适应交直流混联电网中直流系统输送功率变化下发电控制优化决策的要求。
发明内容
本发明的目的是，提出一种权重与约束关联调整的电网实时发电控制优化决策方法，在各种安全约束下，综合考虑发电厂出力对电网安全稳定影响特性，以及发电厂经济环保性能、预测性能、调节性能和现货交易执行情况等，通过设置权重，并在输电设备/断面功率不受限下对相关发电厂出力权重进行调整，实现权重与约束相关联，保障电网发电控制满足实时性、安全性和经济环保要求。
本发明采取的技术方案为：一种权重与约束关联调整的电网实时发电控制优化决策方法，包括：
S1，获取当前电网运行状态数据，内网中各节点注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度，以及内网中的发电厂集合、负荷集合、直流系统交流侧节点集合和内外网联络线集合；
S2，考虑电网安全性能、经济环保性能、预测性能、调节性能，以及现货交易执行情况，计算内网中由当前调控中心控制的各待控发电厂的优化决策综合指标；
S3，根据S2得到的各待控发电厂优化决策综合指标，以及各待控发电厂的出力对输电设备和稳定断面的有功灵敏度，对待控发电厂进行分组；
S4，将各组发电厂分别等值为一个等值发电厂，确定各等值发电厂的并网有功、优化决策综合指标，以及发电厂出力对输电设备/断面的有功灵敏度；
S5，计算各等值发电厂并网有功指令上下限，以及等值发电厂和内网中其它发电厂可用于热备用的有功上下限；
S6，基于预先建立的线性规划模型，对相应的目标函数进行优化求解，得到各等值发电厂的并网有功指令值；
S7，将与S6优化求解结果对应的有功达到限值的输电设备/断面记为受限设备/断面，其它输电设备/断面记为不受限设备/断面；
S8，将对各受限设备/断面的有功灵敏度绝对值皆小于设定值的等值发电厂，作为待重新优化的等值发电厂；若不存在待重新优化的等值发电厂，则转至步骤S11；
S9，对于各待重新优化的等值发电厂，将其实时控制优化决策综合指标选择为不考虑其电网安全性能的综合指标；
S10，基于S6所述预先建立的线性规划模型，在待重新优化的等值发电厂范围内，不考虑各受限设备/断面的有功限额约束，对相应的目标函数优化求解，得到各待重新优化的等值发电厂的并网有功指令值，对S6得到的相应等值发电厂的并网有功指令值进行更新；
S11，将各等值发电厂最终求得的并网有功指令值作为其下一实时控制周期的并网有功指令值，并根据各等值发电厂的并网有功指令值计算对应的各发电厂的下一实时控制周期的并网有功指令值。
优选的，S1包括：
S101，判断当前调控中心是否有上一级调控中心，若是则转至S102，否则转至S103；
S102，获取当前t 0时刻包括内、外网的电网运行状态数据，以t 0时刻本调控中心调度自动化系统状态估计应用功能给出的内网运行状态为基准，对上一级调控中心下发的最新的电网运行状态进行优化调整，生成整合后包括内、外网在内的电网运行状态，记为S 0，基于S 0计算内网中各发电厂、负荷、直流系统交流侧和内网对外联络节点注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度；记内网中的发电厂集合为A、负荷集合为L、直流系统交流侧节点集合DC和内外网联络线集合TL；
S103，获取当前t 0时刻内网的电网运行状态数据，记为S 0，基于S 0计算内网中各发电厂、负荷和直流系统交流侧注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度；记内网中的发电厂集合为A、负荷集合为L、直流系统交流侧节点集合DC和内外网联络线集合TL，并置TL为空集。
优选的，S2中，定义集合A中按调度计划发电的发电厂集合为B，由当前调控中心实时控制的发电厂集合为C，由其他调控中心实时控制的发电厂集合为D，则C中各发电厂的实时控制优化决策综合指标为：
Figure PCTCN2019110363-appb-000001
式中，β i为C中发电厂i的实时控制优化决策综合指标，β s.i、β e.i、β p.i和β c.i分别为当前调控中心调度自动化系统分析得到的发电厂i的安全稳定性能指标、经济环保性能指标、超短期发电能力预测性能指标和有功调节性能指标；W i、W i.0、t s.i和t e.i分别为当前调控中心调度自动化系统分析得到的发电厂i的现货交易计划电量、已完成的现货交易电量、现货交易计划起始时间和现货交易计划结束时间；k s、k e、k p、k c和k t分别为对应安全稳定性能指标、经济环保性能指标、超短期发电能力预测性能指标、有功调节性能指标和现货交易情况的加权系数。
具体的，β s.i、β e.i、β p.i和β c.i分别由调控中心调度自动化系统通过在线安全稳定分析应用功能、电力交易应用功能，以及发电厂运行监视与管理应用功能分析得到；W i、W i.0、t s.i、t e.i由当前调控中心调度自动化系统通过电力交易应用功能分析得到。以上各功能应用可采用调控中心调度自动化系统的现有功能应用。指标β s.i、β e.i、β p.i和β c.i均大于0，数值越大说明相应的性能越好。
S102中，整合后的t 0时刻的内外网运行状态S 0具体通过以下方式得到：首先，基于t 0时刻本调控中心调度自动化系统状态估计应用功能给出的内网运行状态，通过调整上一级调控中心下发的最新的电网运行状态中发电厂并网有功、无功和负荷的有功、无功，以外网中发电厂并网有功调整量平方和、发电厂并网无功调整量平方和、负荷有功调整量平方和以及负荷无功调整量平方和共四者之和最小为优化目标，TL中各回联络线有功偏差绝对值与其输送容量之比都小于设定值ε p和无功偏差绝对值与其输送容量之比都小于设定值ε q为约束，对内、外网的电网运行状态进行整合，对于没有可行解的情况，通过逐步增大ε p、ε q的方式直至获得优化解。
优选的，S3中，对待控发电厂进行分组的公式如下：
Figure PCTCN2019110363-appb-000002
其中，SL为本调控中心负责过载监视输电设备和稳定断面组成的集合，S i.l、S j.l分别为S 0下C中发电厂i、j并网有功对SL中过载监视的输电设备/稳定断面l有功的灵敏度，a为预设的不同发电厂之间实时控制优化决策综合指标的差异门槛值，b为预设的不同发电厂之间并网有功对过载监视的输电设备或稳定断面有功灵敏度的差异门槛值；
将分组后的每组发电机作为一个集合，记待控发电厂分组序列为C 1、C 2、...、C n，n为组数。每组中发电厂数量可大于等于1。
优选的，S4中，采用等值发电厂G 1、G 2、...、G n来等效C 1、C 2、...、C n中的各组发电厂；将S 0下各组中发电厂并网有功之和，作为相应等值发电厂的并网有功；将各组中发电厂的实时控制优化决策综合指标的平均值，作为相应等值发电厂的实时控制优化决策综合指标；针对SL中各个过载监视的输电设备和稳定断面，分别将各组中发电厂的并网有功对SL中过载监视的输电设备和稳定断面有功灵敏度的平均值，作为相应等值发电厂并网有功对SL中过载监视的相同输电设备和稳定断面的有功灵敏度。
优选的，S5中，设实时发电控制周期为T，计及发电厂的并网有功调节速度，各等值发电厂G k在t0+T时刻的并网有功上限P k.1.u和下限P k.1.d为：
Figure PCTCN2019110363-appb-000003
其中，P k.i.max和P k.i.min分别为等值发电厂G k对应的发电厂组C k中发电厂i在t 0+T时刻的并网有功上限和下限；P k.i.0为S 0下C k中发电厂i的并网有功，v k.i.0为S 0下C k中发电厂i的并网有功调节速度；
设发电厂热备用时限为T r，各等值发电厂G k在t 0+T时刻可用于热备用的并网有功上限P k.1.us和下限P k.1.ds为：
Figure PCTCN2019110363-appb-000004
其中，P' k.i.max和P' k.i.min分别等值发电厂C k中发电厂i在t 0+T+T r时刻的并网有功上限和下限；
则集合B/D中的发电厂i在t 0+T时刻可用于热备用的并网有功上限P i1.1.us/P i2.1.us和下限P i1.1.ds/P i2.1.ds为：
Figure PCTCN2019110363-appb-000005
其中，P i1.1.max/P i2.1.max和P i1.1.min/P i2.1.min为集合B/D中发电厂i1/i2在t 0+T+T r时刻的并网有功上限和下限；P i1.1/P i2.1为t 0+T时刻集合B/D中发电厂i1/i2的并网有功计划值；v i1.1/v i2.1为t 0时刻集合B/D中发电厂i1/i2的并网有功调节速度。
优选的，所述预先建立的线性规划模型为：
Figure PCTCN2019110363-appb-000006
其中，β c.k为等值发电厂G k的实时控制优化决策综合指标；P k.0/P k.1为t 0/t 0+T时刻等值 发电厂G k的并网有功/并网有功指令值；P i1.0/P i1.1为t 0/t 0+T时刻B集中发电厂i1的并网有功/有功计划值；P i2.0/P i2.1为t 0/t 0+T时刻D集中发电厂i2的并网有功/有功计划值；P i3.0/P i3.1为TL集中联络线i3注入内网的有功/有功计划值；P i4.0/P i4.1为t 0/t 0+T时刻L集中负荷i4的有功/有功预测值；P i5.0/P i5.1为t 0/t 0+T时刻DC集中交流侧节点i5的并网有功/并网有功计划值；γ为t 0时刻内网的网损系数；f 0和K f分别为t 0时刻内网的频率和有功静态频率特性系数；f r为内网的额定频率；ε f为预设的内网频率允许偏差值；对于SL集中的过载监视输电设备，P sl.l.lmt.FD和P sl.l.lmt.OD的值相等，为按t 0时刻输电设备l的功率因数不变计算得到的输电设备l的有功过载限额；对于SL集中的过载监视稳定断面，P sl.l.lmt.FD和P sl.l.lmt.OD分别为t 0+T时刻稳定断面l的正向稳定限额和反向稳定限额；P sl.l.0为S 0下SL集中的过载监视输电设备或稳定断面l的有功；S C.l.k为S 0下等值发电厂G k并网有功对过载监视的输电设备或稳定断面的有功灵敏度；S B.l.i1/S D.l.i2为S 0下B集/D集中发电厂i1/i2并网有功对过载监视的输电设备或稳定断面l的有功灵敏度；S TL.l.i3为S 0下TL集中联络线i3注入内网有功对过载监视的输电设备或稳定断面l的有功灵敏度；S L.l.i4为S 0下L集中负荷i4的有功对过载监视的输电设备或稳定断面l的有功灵敏度；S DC.l.i5为S 0下DC集中交流侧节点i5的并网有功对过载监视的输电设备或稳定断面l的有功灵敏度；μ u、μ d分别为预设的t 0+T时刻有功正备用容量系数和负备用容量系数。μ u和μ d根据电网调度运行管理规程设置，以内网负荷总量为基准，为现有技术。
优选的，S7中，将S6计算得到的t 0+T时刻等值发电厂G k的并网有功指令值，代入公式(6)中的过载监视的输电设备/稳定断面有功约束方程，将SL中有功达到限值的输电设备、稳定断面组合的集合记为SL1，有功没有达到限值的输电设备、稳定断面组合的集合记为SL2。
S8中，将对各受限设备/断面的有功灵敏度绝对值皆小于设定值ε s的等值发电厂，作为待重新优化的等值发电厂，待重新优化的等值发电厂的集合记为E。
优选的，S9中，对于E中各待重新优化的等值发电厂，将E中所有等值发电厂所对应的发电厂的集合记为EG，则EG中各个发电厂的实时控制优化决策综合指标为：
Figure PCTCN2019110363-appb-000007
将E中各等值发电厂所对应的发电厂的实时控制优化决策综合指标平均值，作为相应的等值发电厂的实时控制优化决策综合指标。
具体的，S10中，将优化求解范围由G替换为E，设备/断面有功限值约束条件的范围由SL调整为SL2，则线性规划模型的具体表示调整为：
Figure PCTCN2019110363-appb-000008
优选的，S11中，对于G中的各等值发电厂：
若P k.1大于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
Figure PCTCN2019110363-appb-000009
为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.max为t 0+T时刻并网有功指令上限，将总量全额分配到等值发电厂G k所对应的各发电厂，得到各个发电厂t 0+T时刻的并网有功指令值；
若P k.1小于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
Figure PCTCN2019110363-appb-000010
作为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.min为t 0+T时刻并网有功指令下 限，将总量全额分配到等值发电厂G k对应的各发电厂，得到各发电厂t 0+T时刻的并网有功指令值。
进一步的，在有功分配过程中，若一次分配不能将总量全额分配完，则去除并网有功指令值达到t 0+T时刻并网有功指令上限或下限的发电厂，将总量中未分配完的余量再次分配给余下的发电厂，并迭代至总量全额分配完；
否则，将等值发电厂G k所对应的各个发电厂S 0下的并网有功分别作为其t 0+T时刻的并网有功指令值。
上述设定值ε取值越小，优化控制的精度越高，对发电厂的调度控制频繁程度越高，反之，优化控制的精度越低，对发电厂的调度控制频繁程度越低，综合权衡优化控制精度和调度控制频繁程度，优选设定值ε取值为0.01。
有益效果
与现有技术相比，本发明具有以下优点和进步：
(1)建立了考虑发电厂出力对电网安全稳定影响特性及其经济环保性能、预测性能、调节性能和现货交易执行情况的线性加权综合指标，权值可由调控中心根据对不同影响因素的重视程度进行灵活设置；
(2)以综合指标与发电厂有功控制指令乘积之和最大化为目标函数，计及发电厂实时有功可调空间和调节速度、输电设备限额、稳定断面正反向限额、调频和调峰等约束，全面反映了实时发电控制优化决策中要考虑安全稳定、经济高效、低碳环保和科学管理等各种因素，满足电力市场环境下交直流大电网多级调度多类电源协调优化实时控制的要求；
(3)通过对与不受限输电设备/断面强相关且与受限输电设备/断面弱相关发电厂的综合指标进行不考虑其出力对电网安全稳定影响特性的调整，实现了发电厂出力优化权重与约束是否达到边界的关联，满足电网安全无约束下以发电厂经济环保性能、预测性能、调节性能和现货交易执行情况为优化权重的实际需求；
(4)通过根据发电厂综合指标和出力对输电设备/断面的灵敏度对发电厂进行分群，有效降低了优化决策变量数目，在保障决策精度的基础上提高了优化决策计算速度。
附图说明
图1所示为本发明一种方法实施例流程示意图。
具体实施方式
以下结合附图和具体实施例进一步描述。
现有的电网实时发电控制优化决策方法中有的考虑了发电厂的经济环保性能、预测性能(新能源发电)、响应调控指令的调节性能和电量交易执行率指标，以这些指标的乘积作为发电厂出力优化的权重，计及了电力平衡、输电设备/断面限额和调峰约束，并考虑了发电厂出力对输电设备/断面的有功灵敏度，通过数学规划算法进行求解，但没有考虑调频约束，没有全面考虑发电厂出力对电网安全稳定的影响特性；有的则以调控中心对发电厂的综合打分作为发电厂出力控制的权先级，虽然在约束条件中增加了调频约束，但只是通过简单的算术来计算发电厂的出力，只适用于简单的辐射性电网。
本发明提出综合考虑发电厂出力对电网安全稳定影响特性及其经济环保性能、预测性能、调节性能和现货交易执行情况，通过对各项指标的线性加权，作为发电厂出力优化的综合指标，各项指标的加权系数可由调控中心根据对不同影响因素的重视程度进行灵活设置，计及发电厂实时有功可调空间和调节速度、输电设备限额、稳定断面正反向限额、调频和调峰等约束，全面反映了实时发电控制优化决策中要考虑安全稳定、经济高效、低碳环保和科学管理等各种因素，满足电力市场环境下交直流大电网多级调度多类电源协调优化实时控制的要求。通过对与不受限输电设备/断面强相关且与受限输电设备/断面弱相关发电厂的综合指标进行不考虑其出力对电网安全稳定影响特性的调整，实现了发电厂出力优化权重与约束是否达到边界的关联，满足电网安全无约束下以发电厂经济环保性能、预测性能、调节性能和现货交易执行情况为优化权重的实际需求，并针对出力向下调节的发电厂忽略其预测性能对综合指标的影响，进一步提高了综合指标的针对性。通过根据发电厂综合指标和出力对输电设备/断面的灵敏度对发电厂进行分群，有效降低了优化决策变量数目，在保障决策精度的基础上提高了优化决策计算速度。
本发明的一种权重与约束关联调整的电网实时发电控制优化决策方法，如图1所示，包括以下步骤：
S1，获取当前电网运行状态数据，内网中各节点注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度，以及内网中的发电厂集合、负荷集合、直流系统交流侧节点集合和内外网联络线集合；
S2，考虑电网安全性能、经济环保性能、预测性能、调节性能，以及现货交易执行情况，计算内网中由当前调控中心控制的各待控发电厂的优化决策综合指标；
S3，根据S2得到的各待控发电厂优化决策综合指标，以及各待控发电厂的出力对输电设备和稳定断面的有功灵敏度，对待控发电厂进行分组；
S4，将各组发电厂分别等值为一个等值发电厂，确定各等值发电厂的并网有功、优化决策综合指标，以及发电厂出力对输电设备/断面的有功灵敏度；
S5，计算各等值发电厂并网有功指令上下限，以及等值发电厂和内网中其它发电厂可用于热备用的有功上下限；
S6，基于预先建立的线性规划模型，对相应的目标函数进行优化求解，得到各等值发电厂的并网有功指令值；
S7，将与S6优化求解结果对应的有功达到限值的输电设备/断面记为受限设备/断面，其它输电设备/断面记为不受限设备/断面；
S8，将对各受限设备/断面的有功灵敏度绝对值皆小于设定值的等值发电厂，作为待重新优化的等值发电厂；若不存在待重新优化的等值发电厂，则转至步骤S11；
S9，对于各待重新优化的等值发电厂，将其实时控制优化决策综合指标选择为不考虑其电网安全性能的综合指标；
S10，基于S6所述预先建立的线性规划模型，在待重新优化的等值发电厂范围内，不考虑各受限设备/断面的有功限额约束，对相应的目标函数优化求解，得到各待重新优化的等值发电厂的并网有功指令值，对S6得到的相应等值发电厂的并网有功指令值进行更新；
S11，将各等值发电厂最终求得的并网有功指令值作为其下一实时控制周期的并网有功指令值，并根据各等值发电厂的并网有功指令值计算对应的各发电厂的下一实时控制周期的并网有功指令值。
实施例
本实施例中，步骤S1中，设电网当前运行时刻为t 0，若本调控中心有上一级调控中心，以t 0时刻本调控中心调度自动化系统状态估计应用功能给出的内网运行状态为基准，对上一级调控中心下发的最新的电网运行状态进行优化调整，生成整合后包括内、外网在内的电网运行状态，记为S 0，并基于S 0计算内网中各个发电厂、负荷、直流系统交流侧节点和内网对外联络节点注入电网的有功对本调控中心负责过载监视的输电设备和稳定断面有功的灵敏度，将内网中发电厂集合记为A，将内网中负荷集合记为L，将内网中直流系统交流侧节点集合记为DC，将内、外网联络线集合记为TL；
若本调控中心没有上一级调控中心，则基于t 0时刻本调控中心调度自动化系统状态估计应用功能给出的电网运行状态，计算电网中各个发电厂、负荷和直流系统交流侧节点注入电网的有功对本调控中心负责过载监视的输电设备和稳定断面有功的灵敏度，将t 0时刻本调控中心调度自动化系统状态估计应用功能给出的电网运行状态记为S 0，将电网中发电厂集合记为A，将电网中负荷集合记为L，将电网中直流系统交流侧节点集合记为DC，将内、外网联络线集合TL置为空集；
其中，内、外网运行状态整合的具体方法为：首先，基于t 0时刻本调控中心调度自动化系统状态估计应用功能给出的内网运行状态，通过调整上一级调控中心下发的最新的电网运行状态中发电厂并网有功、无功和负荷的有功、无功，以外网中发电厂并网有功调整量平方和、发电厂并网无功调整量平方和、负荷有功调整量平方和以及负荷无功调整量平方和共四者之和最小为优化目标，TL中各回联络线有功偏差绝对值与其输送容量之比都小于设定值ε p和无功偏差绝对值与其输送容量之比都小于设定值ε q为约束，对内、外网的电网运行状态进行整合，ε p取值可为0.01、ε q取值可为0.02，对于没有可行解的情况，通过逐步增大ε p、ε q的方式直至获得优化解。
步骤S2，设A中按调度计划发电的发电厂集合为B，A中由本调控中心实时控制的发电厂集合为C，A中由其它调控中心实时控制的发电厂集合为D，A是B、C和D的并集，通过公式(1)计算C中各个发电厂的实时控制优化决策综合指标；
Figure PCTCN2019110363-appb-000011
式中，β i为C中发电厂i的实时控制优化决策综合指标，β s.i为本调控中心调度自动化系统在线安全稳定分析应用功能最新给出的C中发电厂i的安全稳定性能指标，该指标大于0，数值越大表示发电厂并网有功增加对电网的安全稳定性能越好，β e.i为本调控中心调度自动化系统电力交易应用功能最新给出的C中发电厂i的经济环保性能指标，该指标大于0，数值越大表示发电厂的经济环保性能越好，β p.i为本调控中心调度自动化系统发电厂运行监视与 管理应用功能最新给出的C中发电厂i的超短期发电能力预测性能指标，该指标大于0，数值越大表示发电厂的超短期发电能力预测精度越高，β c.i为本调控中心调度自动化系统发电厂运行监视与管理应用功能最新给出的C中发电厂i响应调控中心有功指令的有功调节性能指标，该指标大于0，数值越大表示发电厂响应调控中心有功指令的有功调节性能越好，W i、W i.0、t s.i、t e.i分别为本调控中心调度自动化系统电力交易应用功能最新给出的C中发电厂i的现货交易计划电量、已完成的现货交易电量、现货交易计划起始时间和现货交易计划结束时间，k s、k e、k p、k c和k t分别为调控中心根据对不同影响因素的重视程度而设定的加权系数；
步骤S3，以满足公式(2)作为发电厂分组的判断条件，对C中的发电厂进行分组，对于C中不能与其它发电厂分在同一组的发电厂，分别将每个发电厂单独以1个发电厂作为1个组，将分组后的每组发电厂分别作为一个集合，记为C1、C2、…、Cn，n为组数；
Figure PCTCN2019110363-appb-000012
式中，SL为本调控中心负责过载监视输电设备和稳定断面组成的集合，S i.l、S j.l分别为S 0下C中发电厂i、j并网有功对SL中过载监视的输电设备或稳定断面l有功的灵敏度，a、b分别为设定的发电厂实时控制优化决策综合指标之间的差异门槛值和发电厂并网有功对过载监视的输电设备、稳定断面有功灵敏度之间的差异门槛值；其中，a和b的取值越大，优化决策的时间越短，精度越低，反之，优化决策的时间越长，精度越高，综合权衡优化决策的时间和精度，a通常取值为0.05，b通常取值为0.03。
步骤S4，分别采用等值发电厂G1、G2、…、Gn来代替C1、C2、…、Cn中的发电厂，将等值发电厂的集合记为G，并分别将S0下C1、C2、…、Cn中发电厂并网有功之和作为S0下相应的等值发电厂的并网有功，分别将C1、C2、…、Cn中发电厂的实时控制优化决策综合指标平均值作为相应的等值发电厂的实时控制优化决策综合指标，针对SL中各个过载监视的输电设备、稳定断面，分别将C1、C2、…、Cn中发电厂的并网有功对SL中过载监视的输电设备、稳定断面有功灵敏度的平均值作为相应的等值发电厂并网有功对SL中过载监视的同一个输电设备、稳定断面的有功灵敏度；
步骤S5，设实时发电控制周期为T，计及发电厂的并网有功调节速度，通过公式(3) 计算各个等值发电厂在t 0+T时刻的并网有功上限和下限，设发电厂热备用时限为T r，通过公式(4)计算各个等值发电厂在t 0+T时刻可用于热备用的并网有功上限和下限，通过公式(5)计算出B和D中发电厂在t 0+T时刻可用于热备用的并网有功上限和下限；
Figure PCTCN2019110363-appb-000013
Figure PCTCN2019110363-appb-000014
Figure PCTCN2019110363-appb-000015
式中，P k.1.u、P k.1.d分别为等值发电厂G k在t 0+T时刻的并网有功上限和下限，P k.i.max、P k.i.min分别为等值发电厂G k中发电厂i在t 0+T时刻的并网有功上限和下限，P k.i.0为S0下等值发电厂G k中发电厂i的并网有功，v k.i.0为t 0时刻等值发电厂G k中发电厂i的并网有功调节速度，P' k.i.max、P' k.i.min分别等值发电厂G k中发电厂i在t 0+T+T r时刻的并网有功上限和下限，P k.1.us、P k.1.ds为t 0+T时刻可用于热备用的等值发电厂G k的并网有功上限和下限，P i1.1.max、P i1.1.min分别为B中发电厂i1在t 0+T+T r时刻的并网有功上限和下限，P i1.1为t 0+T时刻B中发电厂i1的并网有功计划值，v i1.1为t 0时刻B中发电厂i1的并网有功调节速度，P i1.1.us、P i1.1.ds分别为t 0+T时刻B中可用于热备用的发电厂i1的并网有功上限和下限，P i2.1.max、P i2.1.min分别为D中发电厂i2在t 0+T+T r时刻的并网有功上限和下限，P i2.1为t 0+T时刻D中发电厂i2的并网有功指令值，v i2.1为t 0时刻D中发电厂i2的并网有功调节速度，P i2.1.us、P i2.1.ds分别为t 0+T时刻D中可用于热备用的发电厂i2的并网有功上限和下限；
步骤S6，通过求解公式(6)表示的优化函数，计算出t 0+T时刻G中各个等值发电厂的并网有功指令值；
Figure PCTCN2019110363-appb-000016
式中，β c.k为等值发电厂k的实时控制优化决策综合指标，P k.1为t 0+T时刻等值发电厂G k的并网有功指令值，P i3.1为t 0+T时刻TL中联络线i3注入内网的有功计划值，P i4.1为t 0+T时刻L中负荷i4的有功预测值，γ为t 0时刻内网的网损系数，f 0和K f分别为t 0时刻内网的频率和有功静态频率特性系数，f r为内网的额定频率，ε f为设定的内网频率允许偏差值，对于SL中的过载监视输电设备，P sl.l.lmt.FD和P sl.l.lmt.OD相等，取为按t 0时刻输电设备l的功率因数不变计算得到的输电设备l的有功过载限额，对于SL中的过载监视稳定断面，P sl.l.lmt.FD和P sl.l.lmt.OD分别为t 0+T时刻稳定断面l的正向稳定限额和反向稳定限额，P sl.l.0为S 0下SL中的过载监视输电设备或稳定断面l的有功，S C.l.k为S 0下等值发电厂G k并网有功对过载监视的输电设备或稳定断面l的有功灵敏度，P k.0为S 0下等值发电厂G k的并网有功，S B.l.i1为S 0下B中发电厂i1并网有功对过载监视的输电设备或稳定断面l的有功灵敏度，P i1.0为S 0下B中发电厂i1的并网有功，S D.l.i2为S 0下D中发电厂i2并网有功对过载监视的输电设备或稳定断面l的有功灵敏度，P i2.0为S 0下D中发电厂i2的并网有功，S TL.l.i3为S 0下TL中联络线i3注入内网有功对过载监视的输电设备或稳定断面l的有功灵敏度，P i3.0为S 0下TL中联络线i3注入内网的有功，S L.l.i4为S 0下L中负荷i4的有功对过载监视的输电设备或稳定断面l的有功灵敏度，P i4.0为S 0下L 中负荷i4的有功，S DC.l.i5为S 0下DC中交流侧节点i5的并网有功对过载监视的输电设备或稳定断面l的有功灵敏度，P i5.0为S 0下DC中交流侧节点i5的并网有功，P i5.1为t 0+T时刻DC中交流侧节点i5的并网有功计划值，μ u、μ d分别为根据电网调度运行管理规程设置的按内网负荷总量为基准的t 0+T时刻有功正备用容量系数和负备用容量系数；
其中，ε f取值越小，优化控制后电网频率偏离额定频率越小，对发电厂的调度控制频繁程度越高，反之，优化控制后电网频率偏离额定频率越大，对发电厂的调度控制频繁程度越低，综合权衡控制后的电网频率偏差和调度控制频繁程度，ε f通常取值为0.02Hz。
步骤S7，将步骤6计算出的t 0+T时刻G中各个等值发电厂的并网有功指令值代入公式(6)中过载监视的输电设备、稳定断面有功约束方程，将SL中有功达到限值的输电设备、稳定断面组合的集合记为SL1，有功没有达到限值的输电设备、稳定断面组合的集合记为SL2；
步骤S8，将G中S0下对SL1中各个输电设备或稳定断面的有功灵敏度绝对值都小于设定值ε s的等值发电厂组合的集合记为E，ε s取值可为0.05。
步骤S9，若E非空，将E中所有等值发电厂所对应的发电厂的集合记为EG，通过公式(7)计算EG中各个发电厂的实时控制优化决策综合指标，并分别将E中各个等值发电厂所对应的发电厂的实时控制优化决策综合指标平均值作为相应的等值发电厂的实时控制优化决策综合指标，否则，进入步骤11；
Figure PCTCN2019110363-appb-000017
步骤S10，通过求解公式(8)表示的优化函数，计算出t 0+T时刻E中各个等值发电厂的并网有功指令值，用于更新步骤S6中计算出的E中等值发电厂的并网有功指令值；
Figure PCTCN2019110363-appb-000018
步骤S11，针对G中各个等值发电厂，若P k.1大于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
Figure PCTCN2019110363-appb-000019
为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.max为t 0+T时刻并网有功指令上限，将总量全额分配到等值发电厂G k所对应的各发电厂，得到各个发电厂t 0+T时刻的并网有功指令值；
若P k.1小于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
Figure PCTCN2019110363-appb-000020
作为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.min为t 0+T时刻并网有功指令下限，将总量全额分配到等值发电厂G k对应的各发电厂，得到各发电厂t 0+T时刻的并网有功指令值。
其中，ε取值越小，优化控制的精度越高，对发电厂的调度控制频繁程度越高，反之，优化控制的精度越低，对发电厂的调度控制频繁程度越低，综合权衡优化控制精度和调度控制频繁程度，ε通常取值为0.01；
在有功分配过程中，若一次分配不能将总量全额分配完，则去除并网有功指令值达到t 0+T时刻并网有功指令上限或下限的发电厂，将总量中未分配完的余量按同样的分配方法再次分配给余下的并网有功指令值未达到t 0+T时刻并网有功指令上限或下限的发电厂，通过迭代，直至总量全额分配完；
否则，将等值发电厂G k所对应的各个发电厂S 0下的并网有功分别作为其t 0+T时刻的并网有功指令值。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
以上结合附图对本发明的实施例进行了描述，但是本发明并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本发明的启示下，在不脱离本发明宗旨和权利要求所保护的范围情况下，还可做出很多形式，这些均属于本发明的保护之内。

Claims (12)

  1. 一种权重与约束关联调整的电网实时发电控制优化决策方法，其特征是，包括：
    S1，获取当前电网运行状态数据，内网中各节点注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度，以及内网中的发电厂集合、负荷集合、直流系统交流侧节点集合和内外网联络线集合；
    S2，考虑电网安全性能、经济环保性能、预测性能、调节性能，以及现货交易执行情况，计算内网中由当前调控中心控制的各待控发电厂的优化决策综合指标；
    S3，根据S2得到的各待控发电厂优化决策综合指标，以及各待控发电厂的出力对输电设备和稳定断面的有功灵敏度，对待控发电厂进行分组；
    S4，将各组发电厂分别等值为一个等值发电厂，确定各等值发电厂的并网有功、优化决策综合指标，以及发电厂出力对输电设备/断面的有功灵敏度；
    S5，计算各等值发电厂并网有功指令上下限，以及等值发电厂和内网中其它发电厂可用于热备用的有功上下限；
    S6，基于预先建立的线性规划模型，对相应的目标函数进行优化求解，得到各等值发电厂的并网有功指令值；
    S7，将与S6优化求解结果对应的有功达到限值的输电设备/断面记为受限设备/断面，其它输电设备/断面记为不受限设备/断面；
    S8，将对各受限设备/断面的有功灵敏度绝对值皆小于设定值的等值发电厂，作为待重新优化的等值发电厂；若不存在待重新优化的等值发电厂，则转至步骤S11；
    S9，对于各待重新优化的等值发电厂，将其实时控制优化决策综合指标选择为不考虑其电网安全性能的综合指标；
    S10，基于S6所述预先建立的线性规划模型，在待重新优化的等值发电厂范围内，不考虑各受限设备/断面的有功限额约束，对相应的目标函数优化求解，得到各待重新优化的等值发电厂的并网有功指令值，对S6得到的相应等值发电厂的并网有功指令值进行更新；
    S11，将各等值发电厂最终求得的并网有功指令值作为其下一实时控制周期的并网有功指令值，并根据各等值发电厂的并网有功指令值计算对应的各发电厂的下一实时控制周期的并网有功指令值。
  2. 根据权利要求1所述的方法，其特征是，S1包括：
    S101，判断当前调控中心是否有上一级调控中心，若是则转至S102，否则转至S103；
    S102，获取当前t 0时刻包括内、外网的电网运行状态数据，以t 0时刻本调控中心调度自 动化系统状态估计应用功能给出的内网运行状态为基准，对上一级调控中心下发的最新的电网运行状态进行优化调整，生成整合后包括内、外网在内的电网运行状态，记为S 0，基于S 0计算内网中各发电厂、负荷、直流系统交流侧和内网对外联络节点注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度；记内网中的发电厂集合为A、负荷集合为L、直流系统交流侧节点集合DC和内外网联络线集合TL；
    S103，获取当前t 0时刻内网的电网运行状态数据，记为S 0，基于S 0计算内网中各发电厂、负荷和直流系统交流侧注入电网的有功对当前调控中心负责过载监视的输电设备和稳定断面有功的灵敏度；记内网中的发电厂集合为A、负荷集合为L、直流系统交流侧节点集合DC和内外网联络线集合TL，并置TL为空集。
  3. 根据权利要求1所述的方法，其特征是，S2中，定义集合A中按调度计划发电的发电厂集合为B，由当前调控中心实时控制的发电厂集合为C，由其他调控中心实时控制的发电厂集合为D，则C中各发电厂的实时控制优化决策综合指标为：
    Figure PCTCN2019110363-appb-100001
    式中，β i为C中发电厂i的实时控制优化决策综合指标，β s.i、β e.i、β p.i和β c.i分别为当前调控中心调度自动化系统分析得到的发电厂i的安全稳定性能指标、经济环保性能指标、超短期发电能力预测性能指标和有功调节性能指标；W i、W i.0、t s.i和t e.i分别为当前调控中心调度自动化系统分析得到的发电厂i的现货交易计划电量、已完成的现货交易电量、现货交易计划起始时间和现货交易计划结束时间；k s、k e、k p、k c和k t分别为对应安全稳定性能指标、经济环保性能指标、超短期发电能力预测性能指标、有功调节性能指标和现货交易情况的加权系数。
  4. 根据权利要求3所述的方法，其特征是，β s.i、β e.i、β p.i和β c.i分别由调控中心调度自动化系统通过在线安全稳定分析应用功能、电力交易应用功能，以及发电厂运行监视与管理应用功能分析得到；W i、W i.0、t s.i、t e.i由当前调控中心调度自动化系统通过电力交易应用功能分析得到。
  5. 根据权利要求1所述的方法，其特征是，S3中，对待控发电厂进行分组的公式如下：
    Figure PCTCN2019110363-appb-100002
    其中，SL为本调控中心负责过载监视输电设备和稳定断面组成的集合，S i.l、S j.l分别为S 0下C中发电厂i、j的并网有功对SL中过载监视的输电设备/稳定断面l有功的灵敏度，a为预设的不同发电厂之间实时控制优化决策综合指标的差异门槛值，b为预设的不同发电厂之间并网有功对过载监视的输电设备或稳定断面有功灵敏度的差异门槛值；
    将分组后的每组发电机作为一个集合，记待控发电厂分组序列为C 1、C 2、...、C n，n为组数。
  6. 根据权利要求5所述的方法，其特征是，S4中，采用等值发电厂G 1、G 2、...、G n来等效C 1、C 2、...、C n中的各组发电厂；将S 0下各组中发电厂并网有功之和，作为相应等值发电厂的并网有功；将各组中发电厂的实时控制优化决策综合指标的平均值，作为相应等值发电厂的实时控制优化决策综合指标；针对SL中各个过载监视的输电设备和稳定断面，分别将各组中发电厂的并网有功对SL中过载监视的输电设备和稳定断面有功灵敏度的平均值，作为相应等值发电厂并网有功对SL中过载监视的相同输电设备和稳定断面的有功灵敏度。
  7. 根据权利要求6所述的方法，其特征是，S5中，设实时发电控制周期为T，计及发电厂的并网有功调节速度，各等值发电厂G k在t 0+T时刻的并网有功上限P k.1.u和下限P k.1.d为：
    Figure PCTCN2019110363-appb-100003
    其中，P k.i.max和P k.i.min分别为等值发电厂G k对应的发电厂组C k中发电厂i在t 0+T时刻的并网有功上限和下限；P k.i.0为S 0下C k中发电厂i的并网有功，v k.i.0为S 0下C k中发电厂i的并网有功调节速度；
    设发电厂热备用时限为T r，各等值发电厂G k在t 0+T时刻可用于热备用的并网有功上限P k.1.us和下限P k.1.ds为：
    Figure PCTCN2019110363-appb-100004
    其中，P' k.i.max和P' k.i.min分别等值发电厂C k中发电厂i在t 0+T+T r时刻的并网有功上限和下限；
    则集合B/D中的发电厂i在t 0+T时刻可用于热备用的并网有功上限P i1.1.us/P i2.1.us和下限P i1.1.ds/P i2.1.ds为：
    Figure PCTCN2019110363-appb-100005
    其中，P i1.1.max/P i2.1.max和P i1.1.min/P i2.1.min为集合B/D中发电厂i1/i2在t 0+T+T r时刻的并网有功上限和下限；P i1.1/P i2.1为t 0+T时刻集合B/D中发电厂i1/i2的并网有功计划值；v i1.1/v i2.1为t 0时刻集合B/D中发电厂i1/i2的并网有功调节速度。
  8. 根据权利要求1所述的方法，其特征是，所述预先建立的线性规划模型为：
    Figure PCTCN2019110363-appb-100006
    其中，β c.k为等值发电厂G k的实时控制优化决策综合指标；P k.0/P k.1为t 0/t 0+T时刻等值发电厂G k的并网有功/并网有功指令值；P i1.0/P i1.1为t 0/t 0+T时刻B集中发电厂i1的并网有功/ 有功计划值；P i2.0/P i2.1为t 0/t 0+T时刻D集中发电厂i2的并网有功/有功计划值；P i3.0/P i3.1为TL集中联络线i3注入内网的有功/有功计划值；P i4.0/P i4.1为t 0/t 0+T时刻L集中负荷i4的有功/有功预测值；P i5.0/P i5.1为t 0/t 0+T时刻DC集中交流侧节点i5的并网有功/并网有功计划值；γ为t 0时刻内网的网损系数；f 0和K f分别为t 0时刻内网的频率和有功静态频率特性系数；f r为内网的额定频率；ε f为预设的内网频率允许偏差值；对于SL集中的过载监视输电设备，P sl.l.lmt.FD和P sl.l.lmt.OD的值相等，为按t 0时刻输电设备l的功率因数不变计算得到的输电设备l的有功过载限额；对于SL集中的过载监视稳定断面，P sl.l.lmt.FD和P sl.l.lmt.OD分别为t 0+T时刻稳定断面l的正向稳定限额和反向稳定限额；P sl.l.0为S 0下SL集中的过载监视输电设备或稳定断面l的有功；S C.l.k为S 0下等值发电厂G k并网有功对过载监视的输电设备或稳定断面的有功灵敏度；S B.l.i1/S D.l.i2为S 0下B集/D集中发电厂i1/i2并网有功对过载监视的输电设备或稳定断面l的有功灵敏度；S TL.l.i3为S 0下TL集中联络线i3注入内网有功对过载监视的输电设备或稳定断面l的有功灵敏度；S L.l.i4为S 0下L集中负荷i4的有功对过载监视的输电设备或稳定断面l的有功灵敏度；S DC.l.i5为S 0下DC集中交流侧节点i5的并网有功对过载监视的输电设备或稳定断面l的有功灵敏度；μ u、μ d分别为预设的t 0+T时刻有功正备用容量系数和负备用容量系数。
  9. 根据权利要求8所述的方法，其特征是，S7中，将S6计算得到的t 0+T时刻等值发电厂G k的并网有功指令值，代入公式(6)中的过载监视的输电设备/稳定断面有功约束方程，将SL中有功达到限值的输电设备、稳定断面组合的集合记为SL1，有功没有达到限值的输电设备、稳定断面组合的集合记为SL2；
    S8中，将对各受限设备/断面的有功灵敏度绝对值皆小于设定值ε s的等值发电厂，作为待重新优化的等值发电厂，待重新优化的等值发电厂的集合记为E。
  10. 根据权利要求9所述的方法，其特征是，S9中，对于E中各待重新优化的等值发电厂，将E中所有等值发电厂所对应的发电厂的集合记为EG，则EG中各个发电厂的实时控制优化决策综合指标为：
    Figure PCTCN2019110363-appb-100007
    将E中各等值发电厂所对应的发电厂的实时控制优化决策综合指标平均值，作为相应的等值发电厂的实时控制优化决策综合指标。
  11. 根据权利要求9所述的方法，其特征是，S11中，对于G中的各等值发电厂：
    若P k.1大于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
    Figure PCTCN2019110363-appb-100008
    为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.max为t 0+T时刻并网有功指令上限，将总量全额分配到等值发电厂G k所对应的各发电厂，得到各个发电厂t 0+T时刻的并网有功指令值；
    若P k.1小于P k.0且(P k.1-P k.0)/P k.1大于设定值ε，则以(P k.1-P k.0)为总量、
    Figure PCTCN2019110363-appb-100009
    作为等值发电厂G k中发电厂i的有功分配系数、P k.i.0为初值、P k.i.min为t 0+T时刻并网有功指令下限，将总量全额分配到等值发电厂G k对应的各发电厂，得到各发电厂t 0+T时刻的并网有功指令值。
  12. 根据权利要求11所述的方法，其特征是，在有功分配过程中，若一次分配不能将总量全额分配完，则去除并网有功指令值达到t 0+T时刻并网有功指令上限或下限的发电厂，将总量中未分配完的余量再次分配给余下的发电厂，并迭代至总量全额分配完；
    否则，将等值发电厂G k所对应的各个发电厂S 0下的并网有功分别作为其t 0+T时刻的并网有功指令值。
PCT/CN2019/110363 2018-10-31 2019-10-10 权重与约束关联调整的电网实时发电控制优化决策方法 WO2020088206A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811286328.9A CN109378863B (zh) 2018-10-31 2018-10-31 权重与约束关联调整的电网实时发电控制优化决策方法
CN201811286328.9 2018-10-31

Publications (1)

Publication Number Publication Date
WO2020088206A1 true WO2020088206A1 (zh) 2020-05-07

Family

ID=65390919

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/110363 WO2020088206A1 (zh) 2018-10-31 2019-10-10 权重与约束关联调整的电网实时发电控制优化决策方法

Country Status (2)

Country Link
CN (1) CN109378863B (zh)
WO (1) WO2020088206A1 (zh)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109378863B (zh) * 2018-10-31 2021-06-01 国电南瑞科技股份有限公司 权重与约束关联调整的电网实时发电控制优化决策方法
CN110970900B (zh) * 2019-12-10 2022-09-20 国电南瑞科技股份有限公司 一种光热机组调相运行提高电压稳定性评价指标计算方法
CN110970901B (zh) * 2019-12-11 2022-09-20 国电南瑞科技股份有限公司 适应波动电源及直流送受端电压安全的控制方法及系统
CN111130149B (zh) * 2020-02-26 2021-07-13 国电南瑞科技股份有限公司 一种考虑性能分布特性的电网发电有功控制方法及系统
CN113469410B (zh) * 2021-05-26 2023-10-31 国电南瑞科技股份有限公司 考虑新能源不确定性的电网最大消纳能力在线计算方法及装置

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140012429A1 (en) * 2012-07-06 2014-01-09 Ian Dempster Systems and methods for balancing an electrical grid with networked buildings
CN106410784A (zh) * 2016-06-02 2017-02-15 国网江西省电力公司赣东北供电分公司 变电站有功负荷对地区电网有功网损的灵敏度计算方法
CN108054790A (zh) * 2017-12-27 2018-05-18 云南电网有限责任公司 基于预测出力逐次逼近的风光发电集群有功实时优化控制方法
CN108321853A (zh) * 2018-03-01 2018-07-24 国电南瑞科技股份有限公司 兼顾调节特性和经济环保性能的电网有功实时控制方法
CN109378863A (zh) * 2018-10-31 2019-02-22 国电南瑞科技股份有限公司 权重与约束关联调整的电网实时发电控制优化决策方法

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102496968A (zh) * 2011-12-20 2012-06-13 国电南瑞科技股份有限公司 间歇式能源与常规能源协调调度模式下发电计划优化方法
CN103401272B (zh) * 2013-06-28 2015-08-12 国电南瑞科技股份有限公司 基于区域协调的光伏电站并网电压控制方法
CN105226685B (zh) * 2015-10-23 2018-10-09 中国电力科学研究院 主动配电网三相有功无功协调的电压相量校正控制方法
JP6709743B2 (ja) * 2017-01-30 2020-06-17 京セラ株式会社 電力変換装置及びその制御方法
CN108123492B (zh) * 2017-12-26 2019-11-22 国网辽宁省电力有限公司 一种考虑火电电蓄热联合调峰的日前发电计划优化方法
CN108520315B (zh) * 2018-03-23 2021-07-23 国电南瑞科技股份有限公司 计及中长期交易和现货交易约束的电网有功实时控制方法
CN108683192B (zh) * 2018-06-27 2022-02-15 广东电网有限责任公司 一种电力现货市场的出清方法、系统、设备及存储介质

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140012429A1 (en) * 2012-07-06 2014-01-09 Ian Dempster Systems and methods for balancing an electrical grid with networked buildings
CN106410784A (zh) * 2016-06-02 2017-02-15 国网江西省电力公司赣东北供电分公司 变电站有功负荷对地区电网有功网损的灵敏度计算方法
CN108054790A (zh) * 2017-12-27 2018-05-18 云南电网有限责任公司 基于预测出力逐次逼近的风光发电集群有功实时优化控制方法
CN108321853A (zh) * 2018-03-01 2018-07-24 国电南瑞科技股份有限公司 兼顾调节特性和经济环保性能的电网有功实时控制方法
CN109378863A (zh) * 2018-10-31 2019-02-22 国电南瑞科技股份有限公司 权重与约束关联调整的电网实时发电控制优化决策方法

Also Published As

Publication number Publication date
CN109378863B (zh) 2021-06-01
CN109378863A (zh) 2019-02-22

Similar Documents

Publication Publication Date Title
WO2020088206A1 (zh) 权重与约束关联调整的电网实时发电控制优化决策方法
CN105846461B (zh) 一种大规模储能电站自适应动态规划的控制方法和系统
WO2017000853A1 (zh) 主动配电网多时间尺度协调优化调度方法和存储介质
CN106505635B (zh) 弃风最小的有功调度模型及调度系统
US20200209812A1 (en) Practical method for short-term operations of super large-scale hydropower plants
CN111092429B (zh) 一种柔性互联配电网的优化调度方法、存储介质及处理器
CN109492861B (zh) 一种梯级水电站群中期电量交易计划分解方法
CN109447405B (zh) 一种承担调峰任务的一库多级式梯级库群短期计划制定方法
CN104181895A (zh) 适应新能源接入的短期与超短期协调滚动调度优化策略
CN113364055B (zh) 一种源网荷储网络化协调频率控制方法
CN107203855B (zh) 含风电系统实时调度的鲁棒两层优化模型及转化等效方法
CN102184472A (zh) 一种基于电网调度侧需求的风水火联合调度方法
Mele et al. Impact of variability, uncertainty and frequency regulation on power system frequency distribution
CN105207253A (zh) 考虑风电及频率不确定性的agc随机动态优化调度方法
CN110247404B (zh) 风电并网电压分层协调控制方法、系统、介质及设备
CN103595061A (zh) 基于综合效益分析的企业电网无功优化方法及系统
CN107528348A (zh) 一种基于来水不确定性的梯级水电站负荷调整方法
CN111130149B (zh) 一种考虑性能分布特性的电网发电有功控制方法及系统
CN104636831B (zh) 一种面向多电网的水电站短期调峰特征值搜索方法
Yang et al. Tracking-dispatch of a combined wind-storage system based on model predictive control and two-layer fuzzy control strategy
Haddi et al. Improved optimal power flow for a power system incorporating wind power generation by using Grey Wolf Optimizer algorithm
Cai et al. Intra-day Tie-line Scheduling Model Considering New Energy Fluctuation
Zhu et al. Hierarchical cluster coordination control strategy for large-scale wind power based on model predictive control and improved multi-time-scale active power dispatching
CN109842160B (zh) 基于两个时点协调优化发电控制的决策方法、装置及系统
Wang et al. Coordinated power smoothing control strategy of multi-wind turbines and energy storage systems in wind farm based on madrl

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19878232

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19878232

Country of ref document: EP

Kind code of ref document: A1