CN115222195A - Power distribution network optimal scheduling method considering source-network-load-storage flexible resources - Google Patents

Power distribution network optimal scheduling method considering source-network-load-storage flexible resources Download PDF

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CN115222195A
CN115222195A CN202210572401.9A CN202210572401A CN115222195A CN 115222195 A CN115222195 A CN 115222195A CN 202210572401 A CN202210572401 A CN 202210572401A CN 115222195 A CN115222195 A CN 115222195A
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郭然龙
邢海军
李安
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Shanghai University of Electric Power
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Abstract

The invention relates to a power distribution network optimal scheduling method considering source-network-load-storage flexible resources, which comprises the following steps of: aiming at different flexible resources, establishing corresponding flexible resource models, wherein the flexible resource models comprise a semi-controlled power supply model, an interruptible load model, an energy storage side model and an SOP model; determining flexibility evaluation indexes, wherein the flexibility evaluation indexes comprise an up-regulation flexibility deficiency index and a down-regulation flexibility deficiency index; constructing a power distribution network optimization scheduling model by setting a target function and constraint conditions based on the flexibility resource model and the flexibility evaluation index; and solving the power distribution network optimal scheduling model to obtain an optimal scheduling solution, and correspondingly controlling the working state of each flexible resource according to the optimal scheduling solution. Compared with the prior art, the invention can effectively improve the flexible adjusting capability of the power system, thereby ensuring the stable, safe and economic operation of the power system.

Description

Power distribution network optimal scheduling method considering source-network-load-storage flexibility resources
Technical Field
The invention relates to the technical field of optimal scheduling of a power distribution network, in particular to an optimal scheduling method of the power distribution network considering source-network-load-storage flexible resources.
Background
With the gradual depletion of traditional fossil energy, at present, new renewable energy sources have been widely applied to power systems, especially wind energy and solar energy, however, since both the wind energy and the solar energy have the characteristics of randomness and volatility, stable operation of the power systems will face a serious challenge.
The installed capacities of wind power and photovoltaic power generation in China are leading to the world, however, the wind abandoning rate and the light abandoning rate are always at a higher point. In recent years, the average wind abandon rate of China is 12.6%, the wind abandon rates of most wind fields in northeast, northeast and northwest regions are about 20%, in order to reduce the wind abandon rate and the light abandon rate of the power system, an energy storage means is mainly adopted and a demand side response mechanism is considered, and the essence is to enhance the flexible adjustment capability of the power system. In the future, high-proportion renewable energy sources inevitably provide higher flexibility requirements for the power system, and from the perspective of optimization scheduling, the traditional optimization scheduling only takes economic optimization as a target, solves an optimal operation strategy in the normal fluctuation range of system voltage, current and power, and does not deeply research from the perspective of flexibility supply and demand, so that the economic efficiency and stability cannot be simultaneously considered in the operation process of the power system.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a power distribution network optimal scheduling method considering source-network-load-storage flexible resources, which can effectively improve the flexible regulation capacity of a power system, thereby ensuring the stable, safe and economic operation of the power system.
The purpose of the invention can be realized by the following technical scheme: a power distribution network optimal scheduling method considering source-network-load-storage flexible resources comprises the following steps:
s1, establishing corresponding flexible resource models aiming at different flexible resources, wherein the flexible resource models comprise a semi-controlled power supply model, an interruptible load model, an energy storage side model and an SOP (Soft Open Point) model;
s2, determining flexibility evaluation indexes, wherein the flexibility evaluation indexes comprise an up-regulation flexibility deficiency index and a down-regulation flexibility deficiency index;
s3, constructing a power distribution network optimal scheduling model by setting a target function and constraint conditions based on the flexibility resource model and the flexibility evaluation index;
and S4, solving the power distribution network optimal scheduling model to obtain an optimal scheduling solution, and correspondingly controlling the working state of each flexible resource according to the optimal scheduling solution.
Further, the semi-controlled power supply model specifically comprises:
f DG,+- (t)＝P DG (t)-P DG (t+τ)
Figure BDA0003659599020000021
wherein, f DG,+- (t) is DG (Distributed Generation ) complete consumption, its flexibility requirement at time t in different directions,
Figure BDA0003659599020000022
for flexibility requirements after wind and light abandonment, P DG,cur And (t) is the abandoned wind and abandoned light power, and tau is the time interval.
Further, the interruptible load model is specifically:
Figure BDA0003659599020000023
wherein, P IL (t) power of the interrupt load for a period of t, h IL (t) is an interrupt variable for interruptible load.
Further, the energy storage side die specifically comprises:
Figure BDA0003659599020000024
wherein S is ESS,k And S ESS,min,k Actual and minimum states of stored energy, E ESS,k To store the capacity of k, h dch,k Is the discharge state (variable 0-1) of stored energy k, P dch,k To discharge power, S ESS,max,k To the maximum state of charge of the stored energy k, h ch,k (t) State of Charge for energy storage at time t, P ch,k And (t) is stored energy charging power.
Further, the SOP model is specifically:
active power transmission limitation:
Figure BDA0003659599020000025
reactive power support limitation:
Figure BDA0003659599020000026
and (3) capacity limitation:
Figure BDA0003659599020000031
wherein w is an SOP mark, E SOP A set of all the SOPs is represented,
Figure BDA0003659599020000032
and
Figure BDA0003659599020000033
the active and reactive power transmitted by the 2 VSCs representing the w-th SOP respectively during the t-th period,
Figure BDA0003659599020000034
Figure BDA0003659599020000035
and
Figure BDA0003659599020000036
the upper and lower limits of reactive power, S, of 2 VSCs representing the w-th SOP w,i And S w,j The mounting capacities of 2 converters of the w-th SOP are shown, respectively.
Further, the index of insufficient flexibility of up-regulation is specifically as follows:
Figure BDA0003659599020000037
Figure BDA0003659599020000038
Figure BDA0003659599020000039
Figure BDA00036595990200000310
F U,s ＝T U,s /T
F U,inf ＝T U,inf /T
wherein,
Figure BDA00036595990200000311
represents the maximum adjustment of stored energy at time t, min P buy,max -P buy (t),U buy τ]Indicating maximum adjustability of main networkForce, N ESS Installing nodes for energy storage, S ESS,k And S ESS,k,max Actual and maximum states of stored energy, E ESS,k To store the capacity of k, h ch,k (t) State of Charge, P, of stored energy at time t ch,k (t) is the stored energy charging power, P buy,max And P buy The maximum output and the actual output of the main network, U buy For the main network ramp rate, (NL (t) -NL (t-1)) is the net load change if F U (t) is greater than or equal to 0, then it represents an upturn flexibility margin; if F U (t)<0, then it represents an insufficient amount of upturn flexibility;
N load represents the load node, Q load,i (t) represents the amount of load shedding at node i at time t;
t is the operating time, T U,s For flexible upturn, with sufficient time, T U,inf To adjust up the time of lack of flexibility, F U,s For flexible upward adjustment, F U,inf To adjust up the rate of lack of flexibility.
Further, the downward regulation flexibility insufficiency index is specifically as follows:
Figure BDA00036595990200000312
Figure BDA0003659599020000041
Figure BDA0003659599020000042
Figure BDA0003659599020000043
F D,s ＝T D,s /T
F D,inf ＝T D,inf /T
wherein S is ESS,k,min Minimum storage for stored energy kState h of dch,k Is the discharge state (0-1 variable) of the stored energy k, P dch,k For discharge power, P buy,min For the minimum output of the main network,
Figure BDA0003659599020000044
for maximum adjustment of interruptible load, N IL For the node where the interruptible load is located, S IL,j Is the interruptible capacity at node j, if F D (t) is greater than or equal to 0, then it represents a turndown flexibility allowance; if F D (t)<0, then it represents an insufficient turndown flexibility;
N DG node of distributed power supply, Q DG,n (t) abandoning the wind and abandoning the light quantity at n nodes at the time t;
T D,s for flexible down-regulation of total time, T D,inf To adjust down the time of insufficient flexibility, F D,s For the purpose of lowering the flexibility margin, F D,inf To adjust the rate of lack of flexibility.
Further, the objective function in step S3 is specifically an objective function with the minimum total cost C, and the calculation formula of the objective function is as follows, in consideration of the operation and maintenance cost, the penalty due to insufficient flexibility, the charge cost for purchasing power on the internet, the network loss cost, and the flexible resource calling cost:
C＝C Ope +C flex +C buy,e +C loss +C a
wherein, C Ope For DG operating maintenance costs, C flex Penalizing costs for lack of flexibility, C buy,e Cost of purchasing electricity to the upper-level grid year by year, C loss For the total annual loss, C a Invoking costs for flexible resources;
the constraint conditions include:
system security constraints, power flow constraints, DG output constraints, energy Storage System (ESS) operation constraints, interruptible load constraints, discrete reactive compensation (capocitors Banks, CB) constraints, static reactive compensation constraints, on-load tap changer (OLTC) operation constraints, and main network output constraints.
Further, the system safety constraint is specifically:
Figure BDA0003659599020000045
wherein, U i,sc,t And U j,sc,t Respectively the voltage values at time t in the sc scenario of nodes i and j,
Figure BDA0003659599020000046
and U is the upper and lower limits of the node voltage, I ij,sc,t Is a branch current at the t moment in sc scene between ij nodes, S ij,sc,t Is the power at time t, S, in sc scene between ij nodes ij,sc,max Is its upper power limit;
the power flow constraint specifically comprises:
Figure BDA0003659599020000051
Figure BDA0003659599020000052
Figure BDA0003659599020000053
P DG,j,sc,t -P load,j,sc,t -P ch,j,sc,t +P dch,j,sc,t +P buy,j,sc,t +P SOP,j,sc,t ＝P j,sc,t
Q DG,j,sc,t -Q load,j,sc,t +Q buy,j,sc,t +Q SOP,j,sc,t +Q CB,n,sc,t +Q SVC,n,sc,t ＝Q j,sc,t
wherein a (j) is a line end node set taking j as an initial node, beta (j) is a line start node set taking j as an end node, and r ij 、x ij And g j 、b j Representing branch impedance and node admittance, V, respectively j,t Is the node voltage magnitude, P DG,j,sc,t Is DG active power output, Q DG,j,sc,t For DG reactive power, P SOP,j,sc,t For active power of SOP, Q SOP,j,sc,t For SOP reactive power, P load,j,sc,t And Q load,j,sc,t Load active and reactive power, Q, at j node respectively CB,n,sc,t For the CB reactive power output at the t moment under the sc scene at the n node, Q SVC,n,sc,t Representing SVC reactive power at the sc scene t moment of the n node;
the DG output constraints are specifically:
Figure BDA0003659599020000054
wherein, P DG,n,max And P DG,n,min Respectively DG at the upper and lower limit of the active power output of the n node, Q DG,n,sc,t 、Q DG,n,max And Q DG,n,min Respectively representing the reactive power output and the reactive upper and lower limits of DG at n nodes;
the operation constraint of the energy storage system is specifically as follows:
Figure BDA0003659599020000055
wherein eta is ch,k Charging efficiency, η, for energy storage k dch,k Discharge efficiency for stored energy k;
the interruptible load constraint is specifically:
Figure BDA0003659599020000056
wherein s is j,t For interrupting the state variable, take the value 0 or 1, delta j Is the maximum reducible rate at node j;
the discrete reactive compensation constraint specifically comprises:
Figure BDA0003659599020000061
wherein N is CB In order to disperse the nodes where the reactive compensation is located,Q CB,unit,n for the compensation power of each group CB, y CB,n,sc,t Number of groups, Y, put into CB at time t of n node CB,n,max Putting an upper limit on the number of CB groups for N nodes, N CB,n,max Is its upper operating limit;
the static reactive compensation constraint specifically comprises:
Figure BDA0003659599020000062
wherein N is SVC Mounting node sets, Q, for SVC SVC,n,max And Q SVC,n,min Upper and lower limits of SVC compensation power at n nodes;
the on-load tap changing OLTC operation constraint is specifically as follows:
Figure BDA0003659599020000063
wherein, V ss For the output voltage regulated by OLTC, σ is the voltage per unit value corresponding to each gear, k max And k min Maximum and minimum ranges for allowable adjustment, respectively;
the main network output force constraint specifically comprises the following steps:
Figure BDA0003659599020000064
wherein R is buy down And R buy up,j,t Respectively the limitation of the up-down climbing rate of the internet, and delta t is a time interval.
Further, the step S4 is specifically to solve the power distribution network optimal scheduling model by using a YALMIP modeling toolkit and a CPLEX solver in the MATLAB environment.
Compared with the prior art, the invention provides an optimized scheduling method considering source-network-load-storage flexibility resources aiming at the problem of insufficient scheduling flexibility of the current power distribution network, and establishes a second-order cone model for power distribution network optimization by taking an economic target as an optimization target and taking the current constraint relaxation technology as a basis by considering node type flexibility resources (source-load-storage) and grid type flexibility resource intelligent soft switches and reactive compensation equipment; therefore, each flexible resource in the system is fully considered, and the set flexibility evaluation index is combined, so that the renewable energy consumption is promoted, the flexibility supply and demand are balanced, the voltage is maintained in a controllable range, the interconnection and intercommunication situation of the source-network-load-storage flexible resources is formed, the optimization of the system performance and economy is realized, and the safe and economic operation of the system is ensured.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of a power distribution network in the embodiment;
FIG. 3 is a schematic diagram of 24-hour load of the distribution network in the embodiment;
FIG. 4a is an optimized scheduling result obtained by the method of the present invention in the embodiment;
FIG. 4b is a diagram illustrating an optimized scheduling result obtained without considering node-type flexible resources in the embodiment;
FIG. 4c is an optimized scheduling result obtained without considering network type flexible resources in the embodiment;
FIG. 5 is a schematic diagram of an average voltage curve of a system corresponding to the method of the present invention and other methods in an embodiment.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Examples
As shown in fig. 1, a method for optimally scheduling a power distribution network considering source-network-load-storage flexibility resources includes the following steps:
s1, establishing corresponding flexible resource models aiming at different flexible resources, wherein the flexible resource models comprise a semi-controlled power supply model, an interruptible load model, an energy storage side model and an SOP model;
s2, determining flexibility evaluation indexes, wherein the flexibility evaluation indexes comprise an up-regulation flexibility deficiency index and a down-regulation flexibility deficiency index;
s3, constructing a power distribution network optimal scheduling model by setting a target function and constraint conditions based on the flexibility resource model and the flexibility evaluation index;
and S4, solving the power distribution network optimal scheduling model to obtain an optimal scheduling solution, and correspondingly controlling the working state of each flexible resource according to the optimal scheduling solution.
The method is applied to practice and mainly comprises the following steps:
1. flexible resource modeling
1) Semi-controlled power supply
A semi-controlled power supply (such as a Wind Turbine Generator (WTG), a Photovoltaic Generator (PVG) and the like) belongs to the category of Distributed power Generation (DG) and mainly comprises a controllable part and an uncontrollable part, wherein the controllable part is a confidence capacity part, and can participate in power balance when a system makes a starting plan, so that the starting capacity of a conventional unit is reduced, and the consumption of renewable energy resources can be effectively promoted. The uncontrollable output part becomes a flexible demand when the output is not adjustable and the balance of the system power supply and demand completely needs other equipment to be adjusted. When the system has insufficient down-regulation flexibility, the system can become a flexible supplier by providing the down-regulation flexibility through wind abandoning, light abandoning and the like. The flexibility requirement calculation formula is as follows:
f DG,+- (t)＝P DG (t)-P DG (t+τ) (1)
Figure BDA0003659599020000081
in the formula: f. of DG,+- (t) the flexibility requirement for DG at time t in different directions when it is completely consumed,
Figure BDA0003659599020000082
for flexibility requirements after wind and light abandonment, P DG,cur And (t) is the abandoned wind and abandoned light power, and tau is the time interval.
2) Interruptible load
The interruptible load reduces the load power of the whole system at certain time intervals by mainly cutting off other loads except the critical load, thereby reducing the requirement of flexible up-regulation, and the expression is
Figure BDA0003659599020000083
In the formula: p IL (t) power of the interrupt load for a period of t, h IL (t) is an interrupt variable that can interrupt the load.
3) Energy storage side
For the evaluation of the energy storage flexibility regulation capability, the time sequence charging and discharging state of the energy storage and the flexibility requirement of the system need to be considered comprehensively, when the system down regulation flexibility requirement is increased sharply, the energy storage charging provides down regulation flexibility for the system at the moment, when the system has the up regulation flexibility requirement, the energy storage equipment adopts a discharging mode to provide up regulation flexibility for the system, and the up regulation and down regulation flexibility which can be provided by the energy storage at any moment is as shown in the following formula:
Figure BDA0003659599020000084
in the formula, S ESS,k And S ESS,min,k Actual and minimum states of stored energy, E ESS,k To store the capacity of k, h dch,k Is the discharge state (variable 0-1) of stored energy k, P dch,k Is the discharge power; s ESS,max,k To the maximum state of charge of the stored energy k, h ch,k (t) State of Charge for energy storage at time t, P ch,k And (t) is stored energy charging power.
4) SOP model
The operational timing optimization model according to SOP includes the following constraints:
active power transmission limitation:
Figure BDA0003659599020000085
reactive power support limitation:
Figure BDA0003659599020000086
and (3) capacity limitation:
Figure BDA0003659599020000091
wherein w is an SOP mark, E SOP A set of all the SOPs is represented,
Figure BDA0003659599020000092
and
Figure BDA0003659599020000093
the active and reactive power transmitted by the 2 VSCs representing the w-th SOP respectively during the t-th period,
Figure BDA0003659599020000094
Figure BDA0003659599020000095
and
Figure BDA0003659599020000096
the upper and lower limits of reactive power, S, of 2 VSCs representing the w-th SOP w,i And S w,j The mounting capacities of 2 converters of the w-th SOP are shown, respectively.
2. Flexibility index
For overall flexibility, the power distribution network is first analyzed for up and down adjustments at various times. When the net load of the distribution system is increased sharply, then
Figure BDA0003659599020000097
In the formula: first item
Figure BDA0003659599020000098
Indicating stored energy at time tMaximum adjustment, second term min [ P buy,max -P buy (t),U buy τ]Indicating the maximum adjustable output of the main network. N is a radical of hydrogen ESS Installing nodes for energy storage; s ESS,k And S ESS,k,max Respectively an energy storage actual electric power storage state and a maximum electric power storage state; e ESS,k Is the capacity of the stored energy k; h is ch,k (t) is the charging state of energy storage at time t; p ch,k (t) is stored energy charging power; p buy,max And P buy Respectively the maximum output and the actual output of the main network; u shape buy The main network climbing rate; (NL (t) -NL (t-1)) is a net load change amount. If F U (t) is greater than or equal to 0, then it represents an upturn flexibility margin; if F U (t)<0, it indicates insufficient upturn flexibility.
Considering the problems of flexibility definition and energy supply quality, the degree of insufficient flexibility of system up-regulation is judged by adopting the loss load of the power distribution network
Figure BDA0003659599020000099
In the formula: n is a radical of load Representing a load node; q load,i (t) represents the amount of load shedding at the inode at time t.
Assuming that the flexible upturn is sufficient for a total time T during the running time T U,s The time with insufficient flexibility of up-regulation is T U,inf Then the flexibility of up-regulation is sufficient for a rate F U,s And an insufficient flexibility rate of up-regulation F U,inf Is composed of
Figure BDA00036595990200000910
Figure BDA00036595990200000911
F U,s ＝T U,s /T (9)
F U,inf ＝T U,inf /T (10)
Similar to the flexibility of up-regulation, when the load in the distribution network decreases, then there is
Figure BDA0003659599020000101
In the formula: s. the ESS,k,min A minimum state of charge for stored energy k; h is dch,k A discharge state (0-1 variable) for stored energy k; p dch,k Is the discharge power; p buy,min Minimum force is applied to the main network;
Figure BDA0003659599020000102
the maximum adjustment amount for interruptible load; n is a radical of IL A node where the load can be interrupted; s IL,j Is the interruptible capacity at node j. F D (t) is greater than or equal to 0, then it represents a turndown flexibility margin; if F D (t)<0, it indicates insufficient turndown flexibility.
Similarly, the wind curtailment and light curtailment quantity of the power distribution network is used as an index for judging the insufficient flexibility of the system during down regulation
Figure BDA0003659599020000103
In the formula: n is a radical of hydrogen DG The node is the node where the distributed power supply is located; q DG,n And (t) the wind curtailment quantity at the node n at the time t.
During this time, the turndown flexibility is sufficient for a total time T D,s And the down-regulation flexibility shortage time is T D,inf Then define a turndown flexibility factor F D,s And adjusting the rate of lack of flexibility F D,inf Comprises the following steps:
Figure BDA0003659599020000104
Figure BDA0003659599020000105
F D,s ＝T D,s /T (15)
F D,inf ＝T D,inf /T (16)
in summary, it can be seen that the flexibility of upturn deficit F U,VAC And adjusting flexibility deficit F D,VAC Comprises the following steps:
Figure BDA0003659599020000106
3. optimal scheduling model for power distribution network
3.1 objective function:
the minimum total cost C is taken as an objective function, and the calculation formula of the minimum total cost C is as follows in consideration of operation maintenance cost, insufficient flexibility punishment, net surfing and electricity purchasing cost, net loss cost and flexible resource calling cost:
C＝C Ope +C flex +C buy,e +C loss +C a (18)
in the formula: c Ope Operating maintenance costs for the DGs; c flex Penalizing costs for lack of flexibility; c buy,e The electricity purchasing cost to the upper-level power grid is annual; c loss The total annual network loss cost; c a The cost is invoked for flexible resources.
3.2 constraint conditions:
1) And (4) system safety constraint:
Figure BDA0003659599020000111
in the formula: u shape i,sc,t And U j,sc,t Voltage values at t moment under the sc scenes of the i node and the j node are respectively;
Figure BDA0003659599020000112
andUthe upper limit and the lower limit of the node voltage are respectively; I.C. A ij,sc,t The branch current at the t moment under the sc scene between the ij nodes is obtained; s ij,sc,t The power at the moment t under the sc scene between the ij nodes is obtained; s ij,sc,max Is its upper power limit.
2) Flow restraint
Figure BDA0003659599020000113
Figure BDA0003659599020000114
Figure BDA0003659599020000115
P DG,j,sc,t -P load,j,sc,t -P ch,j,sc,t +P dch,j,sc,t +P buy,j,sc,t +P SOP,j,sc,t ＝P j,sc,t (23)
Q DG,j,sc,t -Q load,j,sc,t +Q buy,j,sc,t +Q SOP,j,sc,t +Q CB,n,sc,t +Q SVC,n,sc,t ＝Q j,sc,t (24)
In the formula: a (j) is a line end node set taking j as an initial node; β (j) is a line start node set with j as an end node; r is ij 、x ij And g j 、b j Respectively representing branch impedance and node admittance; v j,t Is the node voltage magnitude; p DG,j,sc,t Is DG active power output, Q DG,j,sc,t Reactive power output is given to DG; p SOP,j,sc,t For SOP active power output, Q SOP,j,sc,t The SOP reactive power output is obtained; p load,j,sc,t And Q load,j,sc,t Load active and reactive power at j node respectively; q CB,n,sc,t The reactive power output of CB at the t moment under the sc scene at the n nodes is obtained; q SVC,n,sc,t Representing the SVC reactive power at the n-node sc scene t instant.
3) DG output
Figure BDA0003659599020000116
In the formula: p DG,n,max And P DG,n,min Respectively having active outputs for DG at n nodesAn upper and lower force limit; q DG,n,sc,t 、Q DG,n,max And Q DG,n,min Respectively representing the reactive power output and the reactive upper and lower limits of the DG at the n node.
4) Energy Storage System (ESS) operation constraints:
Figure BDA0003659599020000117
in the formula: eta ch,k Charging efficiency, η, for energy storage k dch,k The discharge efficiency of the stored energy k.
5) Interruptible load constraint:
Figure BDA0003659599020000121
in the formula: s is j,t The value is 0 or 1 for the interrupt state variable; delta. For the preparation of a coating j Is the maximum reducible rate at node j.
6) Discrete reactive compensation (capocitors Banks, CB) constraint:
Figure BDA0003659599020000122
in the formula: n is a radical of CB The node is the node where the discrete reactive compensation is located; q CB,unit,n A compensation power for each group CB; y is CB,n,sc,t Inputting the group number for the time CB of the n nodes at t; y is CB,n,max Putting the upper limit of the number of CB groups for the n nodes; n is a radical of CB,n,max Is the upper limit of its operation.
7) And (3) static reactive compensation constraint:
Figure BDA0003659599020000123
in the formula: n is a radical of SVC Installing a node set for the SVC; q SVC,n,max And Q SVC,n,min Upper and lower limits of SVC compensation power at n nodes.
8) On-load tap changing OLTC operation constraints:
Figure BDA0003659599020000124
in the formula: v ss Is the output voltage regulated by the OLTC; sigma is a voltage per unit value corresponding to each gear; k is a radical of max And k min Maximum and minimum ranges for the allowed adjustment, respectively.
9) Main network output constraint:
Figure BDA0003659599020000125
in the formula, R buy down And R buy up,j,t Respectively, the limitation of the up-down climbing rate of the internet, and delta t is a time interval.
3.3 model processing
In this embodiment, the model is solved by using the YALMIP modeling toolkit in the MATLAB environment and the version 12.8 of the CPLEX solver. To process constraints into SOC representable functions, new variables are introduced
Figure BDA0003659599020000126
The power flow constraint (equations (23) to (25)) can be converted into:
Figure BDA0003659599020000127
Figure BDA0003659599020000131
Figure BDA0003659599020000132
the formula (22) becomes:
Figure BDA0003659599020000133
Figure BDA0003659599020000134
the above equation is then converted to:
Figure BDA0003659599020000135
in the formula, | · the luminance | | 2 As a euclidean norm, it has been shown from prior studies that the relaxation process does not affect the final optimization result, and that the optimal solution must fall on the equation boundary of equation (40).
The simulation verification is carried out by adopting a standard TPC84 node calculation example, the structure diagram of a power distribution network is shown in FIG. 2, the power distribution network system is a three-phase system with the voltage level of 11.4kV, the total load is 25830kW and 20700kVar, the power distribution network system comprises 11 feeders, 83 normally closed switches and 13 normally open switches, and three-phase balance is assumed. The access capacities and positions of WTG and PVG are shown in Table 1, wherein the cut-in wind speed, the rated wind speed and the cut-out wind speed are respectively 3m/s, 11.3m/s and 25m/s, and the rated illumination intensity is 1000W/m 2 。
TABLE 1 DG installation investment parameters
Device Installation node/volume (MW) Operation and maintenance cost/(yuan/kW. H)
WTG 7/3,19/2,28/2 0.032
PVG 50/3,63/2,74/2 0.035
ESS, CB, SVC, OLTC and SOP are original equipment of the system; the ESS installation positions are 27 and 70 nodes, the upper limit of rated power and capacity is 1MW/3MW & h, the charging efficiency and the discharging efficiency are both 0.9, and the upper limit and the lower limit of SOC are [0.1,0.9]. CB installation nodes are 6, 16 and 65, unit compensation capacity is 0.1Mvar, and the maximum input group number is 10; SVCs are installed at nodes 6, 16 and 65, and have compensation power range of [ -0.5,0.5] Mvar; the OLTC is installed at nodes 1 and 11 with a capacity of 50mva,110 + - (8 × 1.25%)/10.5 kV, with a contact initial position of 0, and maintains synchronous regulation. The section switches in the TPC84 algorithm all switch in SOP. The interruptible load nodes are 10, 13, 26, 31, 45, 59, 70, 78, and the maximum cutability rate is 50%.
For the convenience of comparative analysis, a control variable method is adopted to analyze the influence of each device on the system operation, so the embodiment considers the following 4 schemes for optimization:
scheme 1 is a scheduling model provided by the invention;
scheme 2 is to not consider node type flexibility resources (not source-load-store);
scenario 3 does not consider network type flexibility resources (SOP not considered);
scheme 4 does not consider reactive compensation equipment (SVC, CB and OLTC are not considered).
From the results of table 2, it can be seen that the total cost of the scheme 1 is 1711.27 ten thousand yuan less than 2708.05 ten thousand yuan of the scheme 2, wherein the flexibility of the scheme 2 is poor, the penalty cost is 493.93 ten thousand yuan higher than that of the scheme 1 due to insufficient flexibility, and the importance degree of the node type flexibility resource to the economy of the whole system is reflected; the economy of the scheme 3 is inferior to that of the scheme 1 and superior to that of the scheme 2, and compared with the scheme 2, the scheme 3 without considering the SOP reduces the network loss, reduces the electricity purchasing cost and highlights the function of the SOP in the aspect of improving the power flow distribution; the access of the reactive compensation equipment can relieve the problem of insufficient flexibility to a certain extent and reduce the network loss, and after the reactive compensation equipment is not accessed (scheme 4), the punishment cost and the network loss cost due to insufficient flexibility are obviously increased, so that the flexibility is insufficient, and the calling cost is increased due to excessive calling of the flexible resources.
TABLE 2 scheduling fee
Figure BDA0003659599020000141
Fig. 4a to fig. 4c are example scheduling results of each scheme, and the scheme 4 is a change on the reactive side, and the change is not obvious on the active side, which is not shown here. As can be seen from fig. 4a to 4c, the flexible resources such as interruptible load and energy storage can cope with the uncertainty of DG output, provide space for renewable energy consumption, reduce the dependence of the distribution network system on the main network output while ensuring flexibility, improve the power supply diversity degree, and improve reliability. In the scheme 2, node-type flexible resources are not available, so that the overall system has poor capability of coping with uncertainty, and the DG (distributed generation) consumption is reduced rapidly; scheme 3 considers node type flexibility resources but not net rack type flexibility resources, and although the scheduling result is influenced to a certain extent, the DG consumption situation is better than that of scheme 2.
FIG. 5 shows the average system voltage for each case: in the scheme 1, all flexible resources and reactive compensation are considered, so that the time sequence fluctuation of the whole voltage level is relatively smooth, and the voltage quality is obviously improved; in the scheme 2, node type flexibility resources are not considered, and the fluctuation of DG output cannot be well dealt with only by the SOP and reactive compensation equipment, so that the voltage is increased at part of time and the fluctuation is obvious; the network flexibility of the scheme 3 and the scheme 4 is poor, and the voltage stability is poor at the moment that the output of 8.
As can be seen from table 3 in each scheme, in the scheme 1, multiple flexibility resources are considered, so that the flexibility deficiency rate is low, and the situation of insufficient flexibility of up-regulation does not occur; while the insufficient rate of the up-regulation flexibility of the scheme 2 without considering the node type flexibility resources is increased from 0 to 0.6813, and the insufficient rate of the down-regulation flexibility is increased from 0.1355 to 0.5133; compared with the scheme 2, the insufficient up-regulation and down-regulation flexibility rates of the scheme 3 are respectively reduced by 79.23 percent and 36.45 percent, the phenomenon of insufficient flexibility still exists, but the phenomenon is relieved under the action of node type flexibility resources; the flexibility shortage rate of the scheme 4 is close to that of the scheme 1, which shows that the reactive compensation equipment has limited influence on the flexibility adjustment of the active side.
TABLE 3 flexibility index
Scheme(s) Up-regulation of rate of insufficient flexibility Down-regulation of rate of lack of flexibility
Scheme
1 0 0.1355
Scheme 2 0.6813 0.5133
Scheme 3 0.1415 0.3262
Scheme 4 0.0242 0.1512
In the embodiment, by applying the method provided by the invention, a node type flexible resource (source-load-storage) and a grid type flexible resource intelligent Soft Switch (SOP) and reactive power compensation equipment are considered, an economic target is taken as an optimization target, and a second-order cone model for power distribution network optimization is established on the basis of the existing constraint relaxation technology; finally, by combining a TPC (Taiwan Power Company) 84 node calculation example and adopting a CPLEX solver under an MATLAB environment to carry out simulation, the result verifies the effectiveness of the optimization method in improving the economy and the flexible regulation capability.
In summary, the invention considers the flexible resource SOP at the grid side and the node type flexible resource source-load-store at the same time, and the application of the reactive compensation equipment and the OLTC in the power distribution network layer. By example validation analysis, the following conclusions were drawn:
1) In a power distribution system with SOP access, the reactive power vacancy left by insufficient response time or insufficient regulation capacity of reactive compensation equipment can be effectively made up through the real-time regulation of the SOP and the OLTC, the interconnection and intercommunication situation of source-network-load-storage flexible resources can be formed, and the safe and economic operation of the system is ensured.
2) The optimized scheduling method provided by the invention considers the source-network-load-storage flexibility resource at the same time, thereby not only promoting the consumption of renewable energy sources, but also balancing the flexibility supply and demand, maintaining the voltage in a controllable range, and simultaneously realizing the optimization of system performance and economy.

Claims (10)

1. A power distribution network optimal scheduling method considering source-network-load-storage flexibility resources is characterized by comprising the following steps:
s1, establishing corresponding flexible resource models aiming at different flexible resources, wherein the flexible resource models comprise a semi-controlled power supply model, an interruptible load model, an energy storage side model and an SOP model;
s2, determining flexibility evaluation indexes, wherein the flexibility evaluation indexes comprise an up-regulation flexibility deficiency index and a down-regulation flexibility deficiency index;
s3, constructing a power distribution network optimal scheduling model by setting a target function and constraint conditions based on the flexibility resource model and the flexibility evaluation index;
and S4, solving the power distribution network optimal scheduling model to obtain an optimal scheduling solution, and correspondingly controlling the working state of each flexible resource according to the optimal scheduling solution.
2. The optimal scheduling method for the power distribution network considering the source-grid-load-storage flexibility resources as claimed in claim 1, wherein the semi-controlled power model is specifically:
f DG,+- (t)＝P DG (t)-P DG (t+τ)
Figure FDA0003659599010000011
wherein f is DG,+- (t) is the DG complete consumption, its flexibility requirement at time t in different directions,
Figure FDA0003659599010000012
to meet the flexibility requirement after wind and light abandonment DG,cur And (t) is the abandoned wind and abandoned light power, and tau is the time interval.
3. The optimal scheduling method for the power distribution network considering the source-grid-load-storage flexibility resources as claimed in claim 1, wherein the interruptible load model is specifically:
Figure FDA0003659599010000013
wherein, P IL (t) power of the interrupt load for a period of t, h IL (t) is an interrupt variable for interruptible load.
4. The optimal scheduling method of the power distribution network considering the source-grid-load-storage flexibility resources as claimed in claim 1, wherein the energy storage side model is specifically:
Figure FDA0003659599010000014
wherein S is ESS,k And S ESS,min,k Actual and minimum state of charge of the stored energy, E ESS,k To store the capacity of k, h dch,k For the discharge state of the stored energy k, a variable of 0-1 is used for assignment, P dch,k To discharge power, S ESS,max,k To the maximum state of charge of the stored energy k, h ch,k (t) State of Charge for energy storage at time t, P ch,k And (t) is stored energy charging power.
5. The method for optimally scheduling the power distribution network considering the source-network-load-storage flexibility resources as claimed in claim 1, wherein the SOP model specifically comprises:
active power transmission limitation:
Figure FDA0003659599010000021
reactive power support limitation:
Figure FDA0003659599010000022
and (3) capacity limitation:
Figure FDA0003659599010000023
wherein w is an SOP mark, E SOP A set of all the SOPs is represented,
Figure FDA0003659599010000024
and
Figure FDA0003659599010000025
the active and reactive power transmitted by the 2 VSCs representing the w-th SOP respectively during the t-th period,
Figure FDA0003659599010000026
Figure FDA0003659599010000027
and
Figure FDA0003659599010000028
the upper and lower limits of reactive power, S, of 2 VSCs representing the w-th SOP w,i And S w,j The mounting capacities of 2 converters of the w-th SOP are respectively shown.
6. The optimal scheduling method of the power distribution network considering the source-network-load-storage flexibility resources as claimed in claim 1, wherein the insufficient up-regulation flexibility index is specifically:
Figure FDA0003659599010000029
Figure FDA00036595990100000210
Figure FDA00036595990100000211
Figure FDA00036595990100000212
F U,s ＝T U,s /T
F U,inf ＝T U,inf /T
wherein,
Figure FDA00036595990100000213
represents the maximum adjustment of stored energy at time t, min P buy,max -P buy (t),U buy τ]Represents the maximum adjustable output, N, of the main network ESS To storeCan install node, S ESS,k And S ESS,k,max Actual and maximum states of stored energy, E ESS,k To store the capacity of k, h ch,k (t) State of Charge for energy storage at time t, P ch,k (t) is the stored energy charging power, P buy,max And P buy The maximum output and the actual output of the main network, U buy For the main network ramp rate, (NL (t) -NL (t-1)) is the net load change if F U (t) is greater than or equal to 0, then it represents an upturn flexibility margin; if F U (t)<0, then it represents an insufficient amount of upturn flexibility;
N load representing the load node, Q load,i (t) represents the amount of load shedding at the inode at time t;
t is the operating time, T U,s For flexible up-regulation with sufficient total time, T U,inf To adjust up the time for which flexibility is insufficient, F U,s For flexible upward adjustment, F U,inf To adjust up the rate of lack of flexibility.
7. The method for optimally scheduling the power distribution network considering the source-network-load-storage flexibility resources as claimed in claim 6, wherein the down-regulation flexibility deficiency index is specifically as follows:
Figure FDA0003659599010000031
Figure FDA0003659599010000032
Figure FDA0003659599010000033
Figure FDA0003659599010000034
F D,s ＝T D,s /T
F D,inf ＝T D,inf /T
wherein S is ESS,k,min Is the minimum state of charge of the stored energy k, h dch,k Is the discharge state (0-1 variable) of the stored energy k, P dch,k For discharge power, P buy,min For the minimum output of the main network,
Figure FDA0003659599010000035
for maximum adjustment of interruptible load, N IL For the node where the interruptible load is located, S IL,j Is the interruptible capacity at node j, if F D (t) is greater than or equal to 0, then it represents a turndown flexibility allowance; if F D (t)<0, then it represents an insufficient turndown flexibility;
N DG node of distributed power supply, Q DG,n (t) abandoning the wind and abandoning the light quantity at n nodes at the time t;
T D,s for flexible down-regulation of total time, T D,inf To adjust down the time of insufficient flexibility, F D,s For the purpose of lowering the flexibility margin, F D,inf To adjust the rate of lack of flexibility.
8. The method as claimed in claim 1, wherein the objective function in step S3 is specifically an objective function with a minimum total cost C, and the objective function has a calculation formula as follows, taking into account an operation maintenance cost, a penalty for insufficient flexibility, a cost for purchasing electric charge on internet, a network loss cost, and a cost for calling flexible resources:
C＝C Ope +C flex +C buy,e +C loss +C a
wherein, C Ope For DG operating maintenance costs, C flex Penalizing costs for lack of flexibility, C buy,e Purchase cost of electricity to the upper-level power grid for year C loss For annual grid loss, C a Invoking costs for flexible resources;
the constraint conditions include:
system safety constraints, power flow constraints, DG output constraints, energy storage system operation constraints, interruptible load constraints, discrete reactive compensation constraints, static reactive compensation constraints, on-load tap changer (OLTC) operation constraints and main network output constraints.
9. The method for optimally scheduling the power distribution network considering the source-network-load-storage flexibility resources as claimed in claim 8, wherein the system security constraints are specifically:
Figure FDA0003659599010000041
wherein, U i,sc,t And U j,sc,t Respectively the voltage values at time t in the sc scenario of nodes i and j,
Figure FDA0003659599010000042
and U is the upper and lower limits of the node voltage, I ij,sc,t Is a branch current at the t moment in sc scene between ij nodes, S ij,sc,t Is the power at time t, S, in sc scene between ij nodes ij,sc,max Is its upper power limit;
the flow constraint is specifically as follows:
Figure FDA0003659599010000043
Figure FDA0003659599010000044
Figure FDA0003659599010000045
P DG,j,sc,t -P load,j,sc,t -P ch,j,sc,t +P dch,j,sc,t +P buy,j,sc,t +P SOP,j,sc,t ＝P j,sc,t
Q DG,j,sc,t -Q load,j,sc,t +Q buy,j,sc,t +Q SOP,j,sc,t +Q CB,n,sc,t +Q SVC,n,sc,t ＝Q j,sc,t
wherein a (j) is a line end node set taking j as an initial node, β (j) is a line start node set taking j as an end node, r ij 、x ij And g j 、b j Representing branch impedance and node admittance, V, respectively j,t Is the node voltage magnitude, P DG,j,sc,t Is DG active power, Q DG,j,sc,t For DG reactive power, P SOP,j,sc,t For active power of SOP, Q SOP,j,sc,t For SOP reactive power, P load,j,sc,t And Q load,j,sc,t Load active and reactive power, Q, at j node respectively CB,n,sc,t Is the reactive power output of CB at the t moment under the sc scene at the n nodes, Q SVC,n,sc,t Representing SVC reactive power at the sc scene t moment of the n node;
the DG output constraints are specifically:
Figure FDA0003659599010000046
wherein, P DG,n,max And P DG,n,min Respectively being the upper and lower limits of active power output of DG at n node, Q DG,n,sc,t 、Q DG,n,max And Q DG,n,min Respectively representing the reactive power output and the reactive upper and lower limits of the DG at the n node;
the operation constraint of the energy storage system is specifically as follows:
Figure FDA0003659599010000051
wherein eta is ch,k Charging efficiency, η, for energy storage k dch,k Discharge efficiency for stored energy k;
the interruptible load constraint is specifically:
Figure FDA0003659599010000052
wherein s is j,t For interrupt state variables, values of 0 or 1, delta j Is the maximum reducible rate at node j;
the discrete reactive compensation constraint specifically comprises:
Figure FDA0003659599010000053
wherein N is CB For discrete reactive compensation of the node, Q CB,unit,n Compensation power, y, for each group CB CB,n,sc,t Number of groups, Y, put into CB at time t of n node CB,n,max Putting an upper limit on the number of CB groups for N nodes, N CB,n,max Is its upper operating limit;
the static reactive compensation constraint specifically comprises:
Figure FDA0003659599010000054
wherein N is SVC Mounting node set, Q, for SVC SVC,n,max And Q SVC,n,min Upper and lower limits of SVC compensation power at n nodes;
the on-load tap changing OLTC operation constraint is specifically as follows:
Figure FDA0003659599010000055
wherein, V ss For the output voltage regulated by OLTC, σ is the voltage per unit value corresponding to each gear, k max And k min Maximum and minimum ranges for allowable adjustment, respectively;
the main network output force constraint specifically comprises the following steps:
Figure FDA0003659599010000061
wherein R is buy down And R buy up,j,t Respectively, the limitation of the up-down climbing rate of the internet, and delta t is a time interval.
10. The method as claimed in claim 1, wherein the step S4 is specifically to solve the optimal scheduling model of the power distribution network by using a YALMIP modeling kit and a CPLEX solver in a MATLAB environment.
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Publication number Priority date Publication date Assignee Title
CN116522584A (en) * 2023-03-07 2023-08-01 北京智中能源科技发展有限公司 Optimization method for power supply climbing capacity maximization calculation of power distribution network
CN117439090A (en) * 2023-12-19 2024-01-23 浙江大学 Flexible resource allocation or scheduling method taking flexible adjustment coefficient as index

Cited By (4)

* Cited by examiner, † Cited by third party
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CN116522584A (en) * 2023-03-07 2023-08-01 北京智中能源科技发展有限公司 Optimization method for power supply climbing capacity maximization calculation of power distribution network
CN116522584B (en) * 2023-03-07 2023-10-27 北京智中能源科技发展有限公司 Optimization method for power supply climbing capacity maximization calculation of power distribution network
CN117439090A (en) * 2023-12-19 2024-01-23 浙江大学 Flexible resource allocation or scheduling method taking flexible adjustment coefficient as index
CN117439090B (en) * 2023-12-19 2024-04-02 浙江大学 Flexible resource allocation or scheduling method taking flexible adjustment coefficient as index

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