CN110829473A - Power distribution network energy storage optimization configuration method and system considering power four-quadrant output - Google Patents

Power distribution network energy storage optimization configuration method and system considering power four-quadrant output Download PDF

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CN110829473A
CN110829473A CN201911088762.0A CN201911088762A CN110829473A CN 110829473 A CN110829473 A CN 110829473A CN 201911088762 A CN201911088762 A CN 201911088762A CN 110829473 A CN110829473 A CN 110829473A
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bess
power
distribution network
power distribution
node
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张峰
贾兆昊
丁磊
陈玉峰
李华东
张磊
张用
李新梅
陈素红
李明
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State Grid Corp of China SGCC
Shandong University
Electric Power Research Institute of State Grid Shandong Electric Power Co Ltd
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State Grid Corp of China SGCC
Shandong University
Electric Power Research Institute of State Grid Shandong Electric Power Co Ltd
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    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/10—Flexible AC transmission systems [FACTS]

Abstract

The invention discloses a power distribution network energy storage optimal configuration method and system considering power four-quadrant output, which comprises the following steps: establishing a BESS site selection constant volume optimization model by taking the minimum sum of BESS investment operation and maintenance cost and power distribution network operation cost as a target; and setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy for the power distribution network. The invention aims to improve the voltage quality and the economic benefit of a power distribution network, introduces BESS, provides a BESS locating and sizing optimization model based on economic operation modeling of the power distribution network, applies mixed integer second-order cone mathematical programming to optimize and solve the locating and sizing of the BESS, and finally utilizes the rapid and efficient power four-quadrant output capacity of the BESS.

Description

Power distribution network energy storage optimization configuration method and system considering power four-quadrant output
Technical Field
The invention relates to the technical field of power distribution network energy storage optimization configuration, in particular to a power distribution network energy storage optimization configuration method and system considering power four-quadrant output.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, a distributed power supply brings many challenges to a power distribution network, and the voltage quality of the power distribution network can be seriously affected by the fluctuation and randomness of the output of the high-permeability distributed photovoltaic power supply, so that the problems of out-of-limit voltage, severe fluctuation and the like can occur. The Battery Energy Storage System (BESS) has high energy density and fast charge and discharge capability, and can provide an important idea for solving the problems. In addition, the BESS also has the functions of reducing the electric energy transmission loss of the power distribution network, benefiting the system and the like, and is beneficial to improving the economic benefit of the system. Therefore, the research on the optimal configuration of the BESS in the power distribution network is of great significance.
For the research on energy storage site selection and volume fixing at home and abroad, 2 important indexes of voltage deviation and active power network loss are concerned. Essentially, the two belong to the categories of voltage quality and economic benefit respectively. The energy storage can reduce the voltage offset and can also stabilize the voltage fluctuation; in the aspect of economic benefit, the stored energy can reduce the electricity purchasing cost by utilizing the arbitrage mechanism. From the standpoint of the distribution network operator, the stored energy should maximize its utility value after being placed into operation. However, most studies fail to address this when considering planning energy storage in a distribution network; comprehensive contribution of energy storage to voltage quality and economic benefit of the power distribution network is comprehensively measured, so that the power distribution network can ensure high-quality power supply and reduce power supply cost.
Meanwhile, the BESS capacity configuration includes an energy capacity and a power capacity configuration of a Power Conversion System (PCS). The prior art only considers the active power output of the PCS and ignores its capability of reactive power output. In fact, the PCS can perform decoupling control on the output active power and reactive power through the design of a control link of the inverter, so that four-quadrant operation of the output power of the energy storage system is realized. Because the values of the line resistance and the reactance in the power distribution network are in the same order of magnitude, the flow of active power and reactive power respectively affects the electrical parameters (node voltage, active network loss and the like) in the power distribution network. Therefore, if the four-quadrant working mode can be considered when the capacity of the BESS is configured, the BESS can transmit and receive active power and reactive power, and therefore greater benefits of the BESS participating in power distribution network regulation can be achieved.
Disclosure of Invention
In order to solve the problems, the invention provides a power distribution network energy storage optimal configuration method and system considering power four-quadrant output, and provides a location and volume optimal configuration strategy of power four-quadrant operation BESS based on economic operation modeling of a power distribution network. And the nonlinear model is solved by adopting mixed integer second-order cone programming, so that the optimal configuration of the energy storage of the power distribution network is obtained.
In some embodiments, the following technical scheme is adopted:
the power distribution network energy storage optimization configuration method considering power four-quadrant output comprises the following steps:
determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time;
determining the daily network loss of the system according to the current amplitude value flowing through the branch ij at the node i at the time t and the resistance of the branch ij, and converting the daily network loss into economic loss;
establishing a BESS site selection constant volume optimization model by taking the minimum sum of BESS investment operation and maintenance cost and power distribution network operation cost as a target;
and setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy for the power distribution network.
In other embodiments, the following technical solutions are adopted:
a power distribution network energy storage optimization configuration system considering power four-quadrant output comprises:
the device is used for determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time;
the device is used for determining the daily network loss of the system according to the current amplitude value flowing through the branch circuit ij at the node i at the time t and the resistance of the branch circuit ij, and converting the daily network loss into economic loss;
the device is used for establishing a BESS site selection constant volume optimization model by taking the minimum sum of the BESS investment operation and maintenance cost and the power distribution network operation cost as a target;
and the device is used for setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy of the power distribution network.
In other embodiments, the following technical solutions are adopted:
a terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the power storage optimization configuration method of the power distribution network considering power four-quadrant output.
Compared with the prior art, the invention has the beneficial effects that:
the invention aims to improve the voltage quality and the economic benefit of a power distribution network, introduces BESS, provides a BESS locating and sizing optimization model based on economic operation modeling of the power distribution network, applies mixed integer second-order cone mathematical programming to optimize and solve the locating and sizing of the BESS, and finally utilizes the fast and efficient power four-quadrant output capacity of the BESS to realize the following regulation:
1) the arbitrariness is realized by utilizing a time-of-use electricity price mechanism, and the economical efficiency of electricity purchasing of the power distribution network from a superior power grid is improved.
2) The excessive voltage deviation is adjusted, the excessive fluctuation of the node voltage generated by photovoltaic output is stabilized, and the electric energy quality of the power distribution network is improved.
3) The network loss is fully reduced, and the electric energy loss of the power distribution network is reduced.
The invention considers the power four-quadrant output capability of the BESS during the BESS planning, and the result proves that the BESS outputting the power four-quadrant has advantages in participating in the voltage regulation of the power distribution network and reducing the operation cost 2 of the power distribution network compared with the BESS only outputting the active power under the same investment cost, and the potential of the BESS is more excavated in the planning stage, so that the configuration result is more economic and reasonable.
Drawings
Fig. 1 is a schematic diagram of a main circuit structure of a BESS according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of the power four-quadrant output range of the BESS according to one embodiment of the present invention;
FIG. 3 shows a diagram of a first embodiment of the present invention (T)i BESS)0.5The linearization process schematic of (a);
fig. 4(a) - (b) are typical daily load and photovoltaic output curves for the summer season and the winter season, respectively, in the first embodiment of the present invention;
FIG. 5 is a schematic diagram of root node inflow power according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of BESS active power output according to one embodiment of the present invention;
FIG. 7 is a schematic view of the BESS state of charge in accordance with one embodiment of the present invention;
FIG. 8 is a schematic diagram of BESS reactive power output according to one embodiment of the present invention;
FIGS. 9(a) - (c) are schematic diagrams illustrating voltage amplitude variation curves of a photovoltaic grid-connected point according to a first embodiment of the present invention;
fig. 10 is a schematic diagram of the distribution network voltage probability distribution under 3 cases in the first embodiment of the present invention;
fig. 11 is a schematic time distribution diagram of the network loss of the power distribution network in 3 cases in the first embodiment of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example one
In one or more embodiments, a power distribution network energy storage optimization configuration method considering power four-quadrant output is disclosed, which includes the following steps:
determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time; and the active power flowing into the root node from the outside at the time t can be measured by a power measuring instrument.
Determining the daily network loss of the system according to the current amplitude value flowing through the branch ij at the node i at the time t and the resistance of the branch ij, and converting the daily network loss into economic loss; the current amplitude flowing through the branch ij at the node i at the time t can be measured by a current transformer, and the resistance of the branch ij can be measured by a resistance tester.
Establishing a BESS site selection constant volume optimization model by taking the minimum sum of BESS investment operation and maintenance cost and power distribution network operation cost as a target;
and setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy for the power distribution network.
The method described in this example is explained in detail below.
Working principle of 1BESS power four-quadrant grid-connected operation
The BESS consists of a battery storage and a PCS, and the main circuit topology is shown in fig. 1. The battery energy storage device BT releases or absorbs electric energy, PCS is a self-phase-changing three-phase full-bridge inverter, a capacitor C provides direct-current voltage support for the inverter, idcIs a direct side current, ia，ib，icOutputting three-phase current, L, for BESSa，Lb，LcFor equivalent inductance at BESS outlet, Usa，Usb，UscIs the three-phase voltage of the power grid. The independent and rapid adjustment of active power and reactive power can be realized by controlling the on-off of the power electronic device and changing the output voltage and the phase. The BESS controller is generally divided into dual-loop control, an outer loop controller calculates control requirements according to electric quantity data acquired and detected in an actual field, active power and reactive power are subjected to decoupling conversion, a power requirement instruction after final decoupling is sent to an inner loop controller, and the inner loop controller calculates a trigger signal of a device switch according to the obtained instruction to realize four-quadrant real-time adjustment of system output power.
Neglecting the equivalent impedance power loss at BESS no-load, the trajectory of the power exchange between the grid and BESS is approximated as:
Figure BDA0002266229350000041
in the formula: u shapesIs the power supply voltage amplitude of the power grid; u shapetIs alternating current of BESS after inversion by a current converterA magnitude of pressure; zLIs the network impedance.
The power exchange range between the grid and the BESS is shown in fig. 2. At network supply voltage UsAnd impedance ZLIn the determined case, the active power P0And reactive power Q0Is dependent on the BESS output voltage UtMagnitude and phase of.
As can be seen from FIG. 2, UtDetermines the radius of the circle, UtDetermines where on the circle the operating point of the BESS is located.
When an outer ring controller in the PCS detects that active power and reactive power are required by a power distribution network, an inner ring controller controls BESS active power and reactive power to be larger than zero, at the moment, the BESS releases the active power and the reactive power to the power distribution network, a battery is in a discharging state, external reactive power compensation is carried out, and a corresponding BESS working mode is in a 1 st quadrant; when the outer ring controller detects that the active power and the reactive power in the power distribution network are surplus, the inner ring controller controls the active power and the reactive power to be smaller than zero, at the moment, the power grid transmits the active power and the reactive power to the BESS, the battery is in a charging state, the capacitor absorbs the reactive power from the outside, and the corresponding BESS working mode is in a 3 rd quadrant; similarly, the BESS can also work in the 2 nd quadrant or the 4 th quadrant or on the coordinate axis, and the charge-discharge state of the BESS can be flexibly controlled according to the actual requirement.
In the embodiment, the configuration of the BESS is combined with the economic operation optimization of the power distribution network, the operation strategy of the BESS is obtained through the economic optimization on the basis of the typical daily load, and the purpose of minimizing the cost of the power distribution network is achieved under the condition that the set voltage quality of the power distribution network is met.
BESS (beam-Bess optimization system) locating and sizing optimization model based on economic operation modeling of power distribution network
2.1 objective function
For the full-time economic optimization operation of the distribution network in a day, the optimization objective function of the embodiment is set as a single-objective economic function, and the BESS investment operation and maintenance cost FBESSAnd the operating cost of the distribution network (electricity purchase cost F)elecAnd network loss Floss)2 is composed of parts, i.e.
minF＝FBESS+(Felec+Floss) (2)
2.1.1BESS investment, operation and maintenance cost
Figure BDA0002266229350000051
In the formula: f. ofinvInvestment and construction costs for BESS; f. ofmThe operation and maintenance cost of BESS year; c is an equal annual coefficient. The annual investment cost of energy storage is converted into daily calculation, so the denominator is the number of days in one year.
Wherein
Figure BDA0002266229350000052
Figure BDA0002266229350000053
Figure BDA0002266229350000054
In the formula: t isi BESSAnd Ei BESSThe power capacity of the BESS at node i is squared and the battery capacity is measured; k is a radical ofSAnd kEThe price per power capacity and the price per battery capacity of the BESS, respectively; k is a radical ofmMaintaining the tariff rate for BESS operations; r is the discount rate; y is the life years of the BESS.
The decision quantity here is the apparent power capacity S of the BESS at node ii BESSAnd battery capacity Ei BESSHowever, since the apparent power is coupled quadratically with the active and reactive power, the square T of the apparent power capacity is defined to facilitate the processing of the mathematical modeli BESSAs a decision quantity.
2.1.2 economic benefit index function of power distribution network
When the permeability of the distributed power supply in the power distribution network is less than 100%, the power distribution network needs to obtain electric energy from a superior power grid through a root node. The electricity price is adjusted in real time according to the state of the load, the BESS is guided to charge and discharge through the time-of-use electricity price, electricity is purchased and stored when the load is in a low valley state, when the load state reaches a peak value, the electricity price rises, the previously stored electric energy is released, and the BESS arbitrage effect can be achieved.
P for active power flowing from outside by setting time t root node0,tIt is shown that the function of the electricity price with time is αtIf the electricity purchasing cost is as follows:
Figure BDA0002266229350000061
in addition, the network loss is also a large index for measuring the operating economy of the system, and the transmission power inevitably generates loss in the power transmission line, wherein the loss accounts for about 4% -6% of the generated energy. Under the condition that line parameters are not changed, the network loss depends on the amplitude of current flowing through a line, and the flow of active power and reactive power can influence the current amplitude, so that the power exchange between the BESS and a power distribution network can effectively reduce the network loss and the economic loss.
In the network power flow formula, only the voltage amplitude U at the node i at the time t needs to be discussedi,tAnd the amplitude I of the current flowing through branch ijij,tWithout paying attention to the problem of phase angle, the amplitude value is mostly in the form of square in the formula, so that the variable V is in the form of primaryi,tAnd Jij,tInstead of quadratic form of amplitude as decision variable, i.e.
Figure BDA0002266229350000062
Daily loss P of systemlossThe calculation formula is as follows:
Figure BDA0002266229350000064
in the formula: r isijResistance for branch ij; set B is a sectionPoint i and node j can form a set of branches.
The power loss of the network can be converted into economic loss according to the real-time electricity price, namely, the formula (10) can be converted into economic loss
Figure BDA0002266229350000065
2.2 constraint Condition
2.2.1BESS location and volume constraints
For the energy storage configuration of a node i in the power distribution network, the following relational expression is satisfied:
Figure BDA0002266229350000066
Figure BDA0002266229350000067
Figure BDA0002266229350000068
in the formula:
Figure BDA0002266229350000069
a 0-1 variable for a BESS addressing decision at node i; u is the maximum number of configurable BESS in the whole power distribution network; t isi BESS,min，Ti BESS,maxAnd Ei BESS,min，Ei BESS,maxThe square of the BESS power capacity and the lower and upper limits of the battery capacity after the investment cost estimation, respectively.
Too many distributed numbers of BESS cause too high cost, and therefore equation (12) limits the number of installations of BESS. To reduce the amount of computation, a constant T is introducedi BESS,min，Ti BESS,max，Ei BESS,min，Ei BESS,maxThe access position and the capacity configuration parameter of the BESS are constrained by equations (13) and (14).
2.2.2BESS grid-connected operation output constraint
Assuming that the access position of the BESS in the power distribution network is selected and the capacity parameter is configured, the grid-connected operation output of the BESS at the node i and at the time t should meet the following conditions, wherein the active and reactive outputs are limited in the capacity range by the formulas (15) to (18), and the change range of the residual capacity of the energy storage battery is restricted by the formula (19).
Figure BDA0002266229350000072
Figure BDA0002266229350000073
Figure BDA0002266229350000074
Figure BDA0002266229350000075
In the formula:
Figure BDA0002266229350000076
and
Figure BDA0002266229350000077
the charging power, the discharging power, the reactive output and the residual electric quantity of the BESS at the time t of the node i are respectively; sigma is the charge-discharge efficiency of BESS; and D is the maximum appropriate discharge depth of the energy storage battery.
The charging and discharging processes of the BESS cannot be performed simultaneously, i.e.
Figure BDA0002266229350000078
And
Figure BDA0002266229350000079
cannot be simultaneously non-zero values, so that a variable of 0-1 is introducedAnd
Figure BDA00022662293500000711
represents the charge-discharge state of energy storage and satisfies
Figure BDA00022662293500000712
When in use
Figure BDA00022662293500000713
The number of the carbon atoms is 1,
Figure BDA00022662293500000714
when 0, BESS works in a charging state; when in use
Figure BDA00022662293500000715
Is a non-volatile organic compound (I) with a value of 0,
Figure BDA00022662293500000716
when the voltage is 1, BESS works in a discharging state; when in use
Figure BDA00022662293500000717
And
Figure BDA00022662293500000718
at the same time, 0 indicates that node i is not BESS or that time t is neither charging nor discharging.
The output power and the electric quantity of the battery have the following relations:
Figure BDA00022662293500000719
setting the BESS to charge and discharge at △ t with constant power at the initial time t, the power input/output of BESS at node i per unit time step is equal to the variation of the remaining capacity during that time period.
Considering that a daily curve of the charge/discharge operating state of the BESS is obtained by using the typical daily data as the daily data of the whole year, the charge amount and the discharge amount of the BESS are defined to be equal to each other throughout the whole day, that is, the charge amount and the discharge amount are defined to be equal to each other
2.2.3 distributed photovoltaic Power supply constraints
Under the condition of given distributed photovoltaic capacity, the actual output of each photovoltaic power supply is influenced by external factors such as temperature, illumination and the like, the maximum output fluctuates along with the change of time, and the photovoltaic output at the moment t is obtained
Figure BDA0002266229350000082
As a decision quantity, the maximum output is
Figure BDA0002266229350000083
Regardless of the reactive output of the photovoltaic, the model is as follows:
Figure BDA0002266229350000084
2.2.4 network flow constraints
The traditional power distribution network generally has only one power supply, supplies power to a plurality of loads through a power grid, is a typical radial network, and can adopt a distflow model to carry out forward-backward substitution calculation when calculating the power flow[24]. The distflow model is used as a power flow constraint condition of the power distribution network.
For a branch ij in the network, the following relational expression is satisfied, wherein the expressions (24) and (25) are power balance equations at the node j, and the power reference flow direction is from the node i to the node j and from the node j to other nodes; equations (26) and (27) are equations relating the node voltage to the branch current and the branch power.
Figure BDA0002266229350000086
Figure BDA0002266229350000087
Figure BDA0002266229350000088
In the formula: pij,tAnd Qij,tRespectively the active power and the reactive power flowing through the branch ij at the moment t; x is the number ofijReactance for branch ij; r isijJij,tAnd xijJij,tRespectively the active power loss and the reactive power loss on the branch ij at the moment t; u (j) is a set of other nodes connected to the node j except the node i;
Figure BDA0002266229350000089
and
Figure BDA00022662293500000810
respectively the active and reactive power of the load at node j at time t.
2.2.5 System operational safety constraints
In order to prevent voltage deviation from exceeding the limit, voltage fluctuation from being too large and current from exceeding the maximum current-carrying capacity, the following constraints are made:
Figure BDA0002266229350000091
|Vi,t+1-Vi,t|≤4％UNUmax(29)
Figure BDA0002266229350000092
in the formula: u shapeminAnd UmaxRespectively limiting the lower limit and the upper limit of the node voltage; u shapeNIs a voltage reference value; i ismaxIs the maximum ampacity.
With respect to equation (29), the voltage fluctuations in the distribution network cannot be greater than 2% of the reference voltage, according to the relevant standard, i.e.
|Ui,t+1-Ui,t|≤2％UN(31)
And due to
|Ui,t+1+Ui,t|≤2Umax(32)
The expression (29) can be obtained by multiplying the expression (31) and the expression (32) on the left and right sides.
2.3 second order Cone processing of mathematical models
The optimization problem related to the power flow of the power system is a non-convex nonlinear programming problem in nature, and can be calculated and solved by adopting a traditional reliable interior point method. Adding the BESS model without addressing is equivalent to adding integer variables, and the interior point method is not applicable to solving the problem containing discrete variables. The BESS locating and sizing model based on the power distribution network economic operation modeling can adopt mixed integer second-order cone planning, second-order cone processing is carried out on the model from the mathematical perspective, and the global optimal solution of the problem can be obtained by utilizing an algorithm package for solving the cone function.
The cone function comprises an affine set function and a convex set function, common cone functions comprise a first-order linear function, a second-order parabolic function, a second-order norm and the like, an algorithm for solving the mixed integer second-order cone planning generally adopts 2 ideas of an iteration method and a branch-and-bound method, and the mathematical property of the cone function determines that a result obtained after iteration convergence is a global optimal solution.
The decision model proposed herein consists of equations (2) to (7), and equations (11) to (30). It can be seen that the decision variables of the model include integer variables of 0 to 1 and continuous variables, a nonlinear relation exists in the objective function, a non-cone function also appears in the constraint, and the non-cone function needs to be processed to meet the requirement of a second-order cone planning algorithm. The following is the tapering process herein for the non-tapered model described above.
1) The main contradiction in the objective function is Ti BESSThe non-linear nature of the square root term, it is linearized as shown in FIG. 3, where k is1And k2The slopes of two straight lines are respectively.
For accurate linearization results, it is divided into 2 segments and each is processed approximately linearly, thus introducing a piecewise 0-1 variable ηiAnd gammaiAnd will Ti BESSIs divided into (T)i BESS)1And (T)i BESS)2The resulting constraints are as follows:
0≤(Ti BESS)1≤0.25ηi(33)
0.25γi≤(Ti BESS)2≤γi(34)
ηi+γi≤1 (35)
Ti BESS＝(Ti BESS)1+(Ti BESS)2(36)
Figure BDA0002266229350000101
2) in each of the formulae (21), (22) and (24), the form of multiplication of an integer variable and a continuous variable appears, and the M method is used for the treatment.
Introduction of continuous variables
Figure BDA0002266229350000102
And
Figure BDA0002266229350000103
make it satisfy
Figure BDA0002266229350000104
Figure BDA0002266229350000105
Where M can be considered a very large number, this text is taken to meanPower capacity of BESS upper and lower limits. Taking charging power as an example
Figure BDA0002266229350000108
When 0 is taken out, it can be obtained from the formula (38)
Figure BDA0002266229350000109
Is equal to 0, whenWhen 1 is taken out, it can be obtained from the formula (40)
Figure BDA00022662293500001011
Is equal to
Figure BDA00022662293500001012
The discharge power can be converted into continuous variable by the formulas (39) and (41).
3) Subjecting formula (26) to relaxation conversion to obtain
And then carrying out deformation processing on the formula (42) to finally obtain the following second-order norm form:
the equivalence of the model after the relaxation transformation and the original model is described in many documents, the non-convex feasible region of the original problem is relaxed into a convex second-order cone feasible region, the obtained optimal solution is a lower-bound solution of the original problem, if the solution is a point in the original feasible region, the relaxation is strict, and the optimal solution is the optimal solution of the original problem.
3 example simulation and result analysis
3.1 example System and parameter settings
In the embodiment, an IEEE33 node radial distribution network model is adopted as an example to perform simulation verification, the total load of the system is 3.715MW + j2.3Mvar, the rated voltage is 12.66kV, the upper limit and the lower limit of the node voltage are set to +/-5%, and the simulation time step is 15 min. Considering that the load in the network continuously increases along with the time, the annual growth rate of the load is introduced, the value is 3%, typical daily loads in 10 years are accumulated, and the average value is taken as the load level of the final example. Each node adopts the same typical daily load change curve, the nodes 17, 20 and 28 are set as photovoltaic grid-connected points, because the photovoltaic output is closely related to weather factors, and seasonal differences of the loads are considered, in order to reduce calculated amount and ensure the robustness of a power distribution network system, the loads and photovoltaic data of typical days in summer and typical days in winter are selected, wherein the photovoltaic output of the typical days in summer is selected from a day with the largest photovoltaic output fluctuation in summer in 3 years of a certain photovoltaic power station in Shandong province. Typical daily load curves and photovoltaic output are shown in fig. 4(a) - (b).
Selecting a vanadium redox flow battery (VRB) BESS which has advantages in the aspects of price, service life and the like, wherein the current domestic market price is taken as a converter, and the specific parameters are as follows: k is a radical ofSIs 500 yuan/kVA, kEIs 1000 yuan/(kWh.h), kmIs 0.04 and r is 0.1.
Setting BESS maximum installable number U as 2, and BESS maximum power square limit T of each nodei BESS,maxAre all 0.25 (per unit value), the maximum battery capacity limit Ei BESS,maxAll 1 (per unit value), the life y is 10 years, the efficiency sigma is 70%, since the life of the VRB is not affected by the depth of discharge, D is set to 100%, α is set at 08: 00-20: 00 according to the time-of-use electricity price of the urban and rural residents of the electric power company of Shandong province in the national gridt0.5953 yuan/(kWh.h) and 0.3153 yuan/(kWh.h) in the rest period.
3.2 simulation results analysis
3.2.1BESS configuration results and power distribution network economic operation state analysis
The second-order cone programming model is solved by using a Cplex optimization algorithm package developed by IBM corporation of America, and the obtained BESS addressing constant volume optimization result is as follows: access nodes 15 and 30; the BESS battery capacity at the node 15 is 0.5319MW & h, and the power capacity is 0.7100 MVA; the BESS battery capacity at node 30 is 0.3288MW · h, and the power capacity is 0.9452 MVA.
From the aspect of site selection, the nodes 15 and 30 are close to the 2 photovoltaic access nodes 17 and 28, so that the voltage fluctuation of the nodes caused by the sudden change of photovoltaic output can be conveniently adjusted; in addition, the node voltage of the radial distribution network is gradually reduced along the radiation direction, the nodes 15 and 30 are closer to the tail end of the radiation, the BESS is connected to the nodes to improve the voltage level, and the voltage offset is maintained within a set range.
From a constant volume analysis, the node 15 is closer to the radiation end than the node 30, and in order to deal with the more serious voltage deviation problem, the battery capacity of the BESS configuration of the node 15 is larger; the reactive load on the leg on which node 30 is located is heavier and therefore the power capacity of the BESS configuration at node 30 is greater.
From the economic feasibility, the average daily economic operation network loss cost of the distribution network without the BESS is 2018 yuan, the average electricity purchasing cost is 25711 yuan, the average daily economic operation network loss cost of the distribution network after the BESS is configured is 1291 yuan, the average electricity purchasing cost is 25148 yuan, the total daily BESS cost is 915 yuan, the average daily cost is reduced by 375 yuan in total, and the low economic benefit is achieved in the current energy storage market background. Considering that the BESS price generally declines with the technological progress and the industrialized production, the cost is believed to further decline and the technical and economic advantages of energy storage will be more obvious with the continuous updating and upgrading of the energy storage technology in the future.
Because the peak-valley difference of the load is large in typical days in summer and the voltage fluctuation caused by photovoltaic output fluctuation is the largest, the contribution of BESS to the economic operation of the power distribution network is explained by selecting the operation condition of the power distribution network in typical days in summer.
Fig. 5 to 8 show the charge and discharge states of the BESS and the root node power flow state. From the active power change of the root node inflow in fig. 5, it can be seen that, due to the time-of-use electricity price mechanism, the root node inflow active power after the BESS is added is in the range of 00: 00-07: 00 is obviously increased compared with the BESS which is not added, and comparing the change of BESS charging and discharging in the figures 6 and 7, the BESS can be seen to be continuously charged in the low-valley electricity price period and then release the stored electric energy in the peak electricity price period, so as to supply the load demand or participate in the regulation of the distribution network, and realize the arbitrage function; 07: 00-08: 00 active load is continuously increased, in addition, the photovoltaic starts to output power, and BESS is matched with the photovoltaic and the root node to supply power to the load, and the condition of safe operation of the power distribution network is also ensured, so that although the period is a low-valley electricity price period, the BESS is in a discharging state.
As can be seen from fig. 4(a) - (b), the active load is 11: 00, 14: 00, 17: 00 and 20: peak was reached 4 times at 00, photovoltaic was 13: the output power is the largest at 00 hours, and the output power of the photovoltaic is greatly changed for many times in the cloudy weather in the daytime, so that the node voltage, particularly the voltage fluctuation of the photovoltaic grid-connected point, is caused. Fig. 6 shows that BESS achieves active power balance in real time according to load changes and photovoltaic fluctuations by rapid charge and discharge power changes, and alleviates excessive changes in node voltage. In general, the fluctuation of the node voltage is caused by the active output of the photovoltaic, so the active output of the BESS plays a main role in regulation.
In addition, as can be seen from fig. 5, the root node is used as a main power supply for supplying electric energy, the active power and the reactive power of the root node change correspondingly to the change trend of the active load and the reactive load, the active power of the root node changes dramatically during the daytime, because the root node can also play a role in improving the parameters of the power distribution network, when the photovoltaic output fluctuates, the root node can play the same role as the BESS, especially for the grid-connected photovoltaic at the node 20, because no BESS is arranged nearby, the generated node voltage fluctuation is mainly balanced by the root node.
The amplitude variation of the photovoltaic grid-connected node voltage is shown in fig. 9(a) - (c). Wherein, fig. 9(a) is the amplitude change of the 17-node voltage, fig. 9(b) is the amplitude change of the 20-node voltage, and fig. 9(c) is the amplitude change of the 28-node voltage; by observing the voltage amplitude changes at nodes 17 and 28, it is apparent that there are 2 regulatory effects of BESS on the node voltages: firstly, adjusting voltage deviation, and raising the voltage amplitude with the lower voltage limit lower than 0.95 (per unit value) to a set range; secondly, the severe fluctuation of the voltage is stabilized, so that the voltage fluctuation at adjacent moments does not exceed 2% of the rated voltage value. The photovoltaic grid-connected of the node 20 is close to the root node and is mainly influenced by the output power of the root node, so that the BESS is not greatly influenced by the regulation effect.
By combining the analysis, the BESS realizes the power supply matched with the root node and the photovoltaic power generation, thereby not only ensuring the safety of power supply, but also improving the economy of the power distribution network.
3.2.2 Power four quadrant output BESS dominance analysis
In order to test the high efficiency of the power four-quadrant output BESS participating in power distribution network regulation, the BESS of the nodes 15 and 30 is set to only output active power, the determined BESS access position and capacity are set to known quantities, 1 second optimization calculation is carried out on the economic operation state of the power distribution network under the condition of fixed investment, and the results of 2 second optimization under different conditions before and after comparison are carried out. Fig. 10 is a graph of the voltage probability distribution function for all nodes of the distribution network over the day.
As can be seen from fig. 10, the voltage offset can be effectively reduced by adding the power four-quadrant output BESS, and it is found in the simulation process that when the BESS outputs only active power, due to constraints of power flow and lines, the voltage offset cannot be adjusted to 1 ± 5% (per unit), and the reason can be explained by equation (27), which represents the relationship between the voltage of the nodes at the two ends of any branch in the power distribution network and the power flowing through the branch, and it can be seen that the voltage drop on the branch is closely related to both active power and reactive power. In the case of unidirectional radial power flow, if only the magnitude of active power is adjusted, only the voltage drop caused by the active power flow can be reduced, and the voltage drop caused by the reactive power flow still exists and cannot be offset, so that reactive compensation voltage regulation is necessary.
The system loss for the 3 cases versus is shown in fig. 11, except for 20: outside the peak values before and after 00, the overall level of the system network loss after adding the BESS which only outputs the active power does not fall and reversely rises, because the BESS properly boosts the terminal voltage by releasing the active power, thereby causing the increase of the network loss; and BESS of power four-quadrant output can avoid unnecessary electric energy loss through the reactive power voltage regulation, and can observe from the figure that its net loss has reduced by a wide margin. The size of the network loss directly depends on the size of the current amplitude of the line, the equation (26) shows that the current amplitude of the line is positively correlated with the flowing active power and reactive power of the line, and is negatively correlated with the voltage of a first node, if only the active power is regulated on the power distribution network, only the active power part of the line can be reduced, and in addition, the voltage of each node which is regulated only by the active power is integrally lower than that of a power four-quadrant. For all of the above reasons, the total network loss of the net active regulation result will naturally be relatively high.
The power distribution network regulation effects of the BESS which only outputs active power and BESS power under 2 conditions of four-quadrant output are compared from the aspects of voltage regulation and economic benefits, and the superiority of the power four-quadrant output BESS provided by the text participating in power distribution network regulation is verified.
Example two
In one or more embodiments, a power distribution network energy storage optimization configuration system considering power four-quadrant output is disclosed, comprising:
the device is used for determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time;
the device is used for determining the daily network loss of the system according to the current amplitude value flowing through the branch circuit ij at the node i at the time t and the resistance of the branch circuit ij, and converting the daily network loss into economic loss;
the device is used for establishing a BESS site selection constant volume optimization model by taking the minimum sum of the BESS investment operation and maintenance cost and the power distribution network operation cost as a target;
and the device is used for setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy of the power distribution network.
In other embodiments, a terminal device is disclosed that includes a processor and a computer-readable storage medium, the processor to implement instructions; the computer readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the power storage optimization configuration method of the power distribution network considering power four-quadrant output in the first embodiment.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.

Claims (10)

1. The power distribution network energy storage optimal configuration method considering power four-quadrant output is characterized by comprising the following steps:
determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time;
determining the daily network loss of the system according to the current amplitude value flowing through the branch ij at the node i at the time t and the resistance of the branch ij, and converting the daily network loss into economic loss;
establishing a BESS site selection constant volume optimization model by taking the minimum sum of BESS investment operation and maintenance cost and power distribution network operation cost as a target;
and setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy for the power distribution network.
2. The method according to claim 1, wherein the electricity purchase cost is determined according to a function of active power flowing from the outside at the root node at the time t and a change of electricity price with time, specifically:
Figure FDA0002266229340000011
wherein, FelecFor purchase of electricity cost, P0,tRepresenting the real power flowing from the outside into the root node at time t, αtRepresenting a function of electricity prices over time.
3. The method for optimally configuring energy storage of the power distribution network considering power four-quadrant output according to claim 1, wherein the daily network loss of the system is determined according to the current amplitude flowing through the branch ij at the node i at the time t and the resistance of the branch ij, and specifically comprises the following steps:
Figure FDA0002266229340000012
wherein r isijResistance for branch ij; set B is a set where node i and node j can form a branch,
Figure FDA0002266229340000013
Iij,tthe magnitude of the current flowing through branch ij at node i is time t.
4. The method for optimally configuring energy storage of the power distribution network considering power four-quadrant output according to claim 1, wherein the daily network loss is converted into economic loss, specifically:
Figure FDA0002266229340000014
wherein r isijResistance for branch ij; set B is a set where node i and node j can form a branch,Iij,tthe magnitude of the current flowing through branch ij at node i at time t, αtRepresenting a function of electricity prices over time.
5. The method for optimal configuration of energy storage of a power distribution network considering power four-quadrant output according to claim 1, wherein a Best Effort (BESS) site selection constant volume optimization model is established with a target of minimum sum of BESS investment operation and maintenance cost and power distribution network operation cost, and specifically comprises the following steps:
min F＝FBESS+(Felec+Floss)
wherein，FBESSFor BESS investment operation and maintenance costs, FelecTo purchase electricity cost, FlossThe economic loss caused by the network loss.
6. The optimal configuration method for energy storage of the power distribution network considering power four-quadrant output according to claim 5, wherein the BESS investment operation and maintenance cost specifically comprises:
Figure FDA0002266229340000021
wherein f isinvInvestment and construction costs for BESS; f. ofmThe operation and maintenance cost of BESS year; c is an equal annual coefficient.
7. The method for optimally configuring the energy storage of the power distribution network considering the power four-quadrant output according to claim 1, wherein constraint conditions are set for the deviation and fluctuation range of the voltage of each node, and specifically comprises the following steps: BESS location and volume fixing constraint, BESS grid-connected operation output constraint, distributed photovoltaic power supply constraint, network power flow constraint and system operation safety constraint.
8. The optimal configuration method for energy storage of the power distribution network considering power four-quadrant output according to claim 1, wherein the best solution is performed on the BESS localization constant volume optimization model by using mixed integer second order cone mathematical programming, and specifically comprises the following steps:
carrying out cone processing on 0-1 integer variables, continuous variables, nonlinear relational expressions and non-cone functions in constraints in a BESS (Bess site selection constant volume) optimization model from the mathematical angle by adopting a mixed integer second-order cone programming;
the global optimal solution of the problem can be obtained by utilizing the algorithm package of solving the cone function.
9. Consider distribution network energy storage optimal configuration system of power four-quadrant output, its characterized in that includes:
the device is used for determining the electricity purchasing cost according to the active power flowing from the outside by the root node at the time t and the function of the electricity price changing along with the time;
the device is used for determining the daily network loss of the system according to the current amplitude value flowing through the branch circuit ij at the node i at the time t and the resistance of the branch circuit ij, and converting the daily network loss into economic loss;
the device is used for establishing a BESS site selection constant volume optimization model by taking the minimum sum of the BESS investment operation and maintenance cost and the power distribution network operation cost as a target;
and the device is used for setting constraint conditions for the deviation and fluctuation range of each node voltage, and performing optimization solution on the BESS locating and sizing optimization model by using mixed integer second-order cone mathematical programming to obtain an optimal BESS locating and sizing strategy of the power distribution network.
10. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer-readable storage medium is used for storing a plurality of instructions, wherein the instructions are adapted to be loaded by a processor and execute the method for optimizing the energy storage of a power distribution network considering power four-quadrant output according to any one of claims 1 to 8.
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