CN116404693A - Active and reactive power coordination loss reduction control method and device considering source network load storage - Google Patents
Active and reactive power coordination loss reduction control method and device considering source network load storage Download PDFInfo
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- 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
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/50—Controlling the sharing of the out-of-phase component
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
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Abstract
The invention discloses an active and reactive power coordination loss reduction control method and device considering source network load storage, comprising the following steps: establishing a new energy source access power grid system to be optimized, wherein basic parameters of the system comprise node injection power, branch parameters, initial transformer ratio, wind power output curve and photovoltaic output curve; according to basic parameters of the system, an active reactive power coordination multi-objective optimization model with minimum system operation network loss and voltage offset is established; solving an active and reactive coordination multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal solution set; and adjusting the control variable of the system based on the Pareto optimal solution set to realize active and reactive power coordination loss reduction control of the new energy access to the power grid. The active and reactive coordination optimization of the power grid can be realized, the electric energy quality of the system is improved, the new energy output is smoothed, and the power grid loss is reduced.
Description
Technical Field
The invention belongs to the technical field of operation control methods of power systems, relates to an active and reactive power coordinated loss reduction control method considering source network load storage, and further relates to an active and reactive power coordinated loss reduction control device considering source network load storage.
Background
With the rapid development of the economy in China, renewable energy power generation is rapidly developed, the power load is continuously increased, and the traditional resources are increasingly deficient. Renewable energy power generation is greatly influenced by natural factors such as weather temperature, humidity and the like, has strong volatility, intermittence and randomness, and the output power of the renewable energy power generation is difficult to control. The continuous access of large-scale new energy causes the structure of the power system to be more and more complex, and has larger influence on the aspects of system tide distribution, electric energy quality, voltage distribution, voltage stability, network loss and the like, thereby bringing great challenges to the safe and stable operation of the power grid.
At present, under the background that new energy power generation is accessed to a power grid in a large scale, how to safely and efficiently realize the stability of the loss reduction control voltage of the power grid becomes a hot research problem. In the aspect of optimizing operation of a power grid, most of researches at present optimize new energy access to the power grid from reactive power, neglect the action of smooth distributed power supply output fluctuation of source network load storage interaction, and do not fully consider the influence of active and reactive power coupling coordination optimization on economic and safe operation of the power grid, so that the power grid loss is large.
Disclosure of Invention
The invention aims to provide an active and reactive power coordination loss reduction control method considering source network load storage, which solves the problem of larger power grid loss in the prior art.
The technical scheme adopted by the invention is that the active and reactive power coordination loss reduction control method considering the source network load storage comprises the following steps:
step 1, establishing a new energy source access power grid system to be optimized, wherein basic parameters of the system comprise node injection power, branch parameters, initial transformer ratio, wind power output curve and photovoltaic output curve;
and 4, adjusting control variables of the system based on the Pareto optimal solution set, and realizing active and reactive power coordination loss reduction control of the new energy access grid.
The invention is also characterized in that:
the objective function of the active-reactive coordination multi-objective optimization model is as follows:
in the above, N L And N T Respectively representing the number of branches and transformers, T is the scheduling total time period, deltaT is the time length of each time period, and P Loss (l, t) is the loss of branch l or transformer at t time, g l ＝r l /(r 2 l +x 2 l )，r l +jx l For the impedance of branch l, P iw,t Wind power injection power of node i at time t，P iv,t Represents the photovoltaic injection power of node i at time t,
load power representing an unregulated load connected to node i, < >>
Load power, U, representing the adjustable load connected to node i i,t For the voltage amplitude of node i of period t, U ei Is the rated voltage of node i.
The constraint conditions of the active and reactive coordination multi-objective optimization model comprise a power balance constraint condition, a power flow constraint condition, a reactive compensation constraint condition, a power supply output constraint, an energy storage system constraint condition, an interruptible load constraint condition and a transferable load constraint condition.
The constraint conditions of the active and reactive coordination multi-objective optimization model are specifically as follows:
power balance constraint:
in the above, P i,t 、Q i,t Active power and reactive power at node i at time t respectively,
active power and reactive power of conventional load of node i at t moment, P RE,i,t 、Q RE,i,t Active power and reactive power of wind power and photovoltaic injection node i at t moment respectively, +.>
Active power, reactive power and Q of i node adjustable load at t moment C,i,t Representing reactive power provided by a reactive compensation device at a node i at a moment t, and P LOSS,i,t Representing the network loss of node i at time t, P ESS,i,t Representing the active power stored by the node i at the moment t;
load flow constraint conditions:
in the above, U i,t 、U j,t Representing the voltage magnitudes of i node and j node in the system, θ ij 、G ij 、B ij Respectively representing phase angle difference, conductance and susceptance between the node i and the node j;
expression of inequality constraint:
in the above, N g U, which is the number of generators in the system i,max 、U i,min P is the upper and lower limit value of the generator terminal voltage gi,max 、P gi,min The upper limit value and the lower limit value of the active output of the generator are used; q (Q) gi,max 、Q gi,min The upper limit value and the lower limit value of reactive output of the generator are used;
the upper limit and the lower limit of the voltage of the node i are respectively;
reactive compensation constraint conditions:
in the above, Q Ci,min 、Q Ci,max Respectively represents the minimum and maximum switching capacity of the reactive compensation device, T ki,min 、T ki,max Respectively representing minimum and maximum reactive power of gears of on-load voltage-regulating transformer, S C 、S k Respectively a node set where the switchable capacitor and the on-load voltage regulating transformer are located;
power supply output constraint conditions:
in the above-mentioned method, the step of,
the maximum power generation output is the photoelectric power in the t period; />
For t period of photoelectric output, < >>
Maximum power generation output of the wind power in the t period; />
Wind power output is t time period;
constraint conditions of the energy storage system:
in the above, SOC 0 For storing the SOC value at the initial moment, P ch 、P dis The charge and discharge power between t and t-1 time periods respectively is at most 0, eta ch And eta dis Respectively charge and discharge efficiency, delta t is a continuous time period of charge and discharge, S rate Is the rated capacity of energy storage;
state of charge upper and lower limit constraints:
SOC ESSi,min ≤SOC ESSi (t)≤SOC ESSi,max (8)；
in the above, SOC ESSi,min And SOC (System on chip) ESSi,max Respectively the minimum value and the maximum value allowed by the ith energy storage SOC;
upper and lower limit constraint of energy storage charging and discharging power:
in the above, P ch,max And P dis,max Respectively storing energy of the maximum charging power and the maximum discharging power;
constraints on interruptible load:
in the above-mentioned method, the step of,
to the maximum and minimum interrupt capacity of interruptible load, P IL,i,t The interrupt capacity of the ith interruptible load at the T moment, T IL,i Interrupt time for the ith interruptible load user, < +.>
Minimum and maximum interrupt time for the ith interruptible load user, N IL,i For the number of interruptions of the ith interruptible user, < >>
The maximum interruption times of the ith interruption user;
constraint that load can be transferred:
in the above, P trl (t)、P trb (t) the upper and lower limits of the total transferable loads,
the total transferable loads before and after the transfer at the moment t are respectively; />
Respectively, the upper part of the transferable load and the transferable time rangeLower limit, M tr,i 、M tr,i The transferable load transfer amount and the capacity, respectively.
And 4, controlling variables including generator terminal voltage, transformer transformation ratio, reactive power compensation device switching capacity, energy storage system charging and discharging strategy and flexible load input.
The invention further aims to provide an active and reactive power coordination loss reduction control device considering source network load storage.
The invention adopts another technical scheme that the active and reactive power coordination loss reduction control device considering the source network load storage comprises:
the system comprises a parameter acquisition module, a power generation module and a photovoltaic output module, wherein the parameter acquisition module is used for establishing a new energy source to be connected into a system to be optimized of a power grid, and basic parameters of the system comprise node injection power, branch parameters, an initial transformer ratio, a wind power output curve and a photovoltaic output curve;
the model building module is used for building an active reactive coordination multi-objective optimization model with minimum system operation network loss and voltage offset according to the basic parameters of the system;
the solution control module is used for solving the active and reactive coordination multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal solution set;
and the variable control module is used for adjusting the control variable of the system based on the Pareto optimal solution set and realizing active and reactive power coordination loss reduction control of the new energy access power grid.
The beneficial effects of the invention are as follows: according to the active and reactive power coordination loss reduction control method considering the source network load storage, an active and reactive power coordination multi-objective optimization model with minimum system operation loss and voltage deviation is established based on wind power, photovoltaic, load and energy storage parameters, the reactive capacity of a reactive power supply, the active adjustment capacity of an energy storage device and a flexible load are utilized, an optimal solution set is solved by adopting a multi-objective particle swarm optimization algorithm, an optimal solution is selected, and an optimal control scheme can be objectively provided, so that the active and reactive power coordination optimization of a power grid is realized, the electric energy quality and the gentle new energy output of the system are improved, and the power grid loss is reduced.
Drawings
FIG. 1 is a flow chart of an active and reactive power coordinated loss reduction control method taking source network load storage into consideration;
FIG. 2 is a schematic diagram of the topology of the IEEE-30 node system after modification in the active and reactive power coordination loss reduction control method taking into account the source network load storage;
FIG. 3 is a schematic diagram of the distribution of pareto solutions in the algorithm of the active-reactive coordination loss reduction control method taking the source network charge storage into consideration;
fig. 4 is a diagram showing the comparison of network losses before and after system optimization in the active-reactive coordination loss reduction control method considering the source network load storage;
FIG. 5 is a schematic diagram showing the comparison of loads before and after system optimization in the active-reactive coordination loss reduction control method considering the source network load storage;
FIG. 6 is a graph of load shedding in the active-reactive power coordinated loss reduction control method taking into account the source network load storage;
fig. 7 is a schematic diagram of a charge-discharge strategy and a charge state change curve of an energy storage system after optimization in an active-reactive coordination loss reduction control method considering source network charge storage.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
The invention relates to an active and reactive coordination loss reduction control method for source network charge storage, wherein the interaction form of the source network charge storage comprises source complementation, source network coordination, source storage interaction, network storage interaction, charge storage interaction, network charge interaction, source charge interaction and the like. The source complementation can make up the defects of randomness and fluctuation of single renewable energy sources, improves the utilization rate of renewable energy sources, and ensures that the system has self-regulating capability. The flexible load plays a role in balancing intermittent energy power fluctuation in source-load interaction, improves the digestion capacity of a power supply side, and ensures the economical efficiency of the system. Network load interaction reduces loss on a transmission line through the adjustment of reactive power measurement of a power grid, and participates in power grid regulation through energy interaction of interruptible load and transferable load with the power grid. The flexible load is divided into interruptible load and transferable load: a) The interruptible load refers to load which cuts down a load curve to a certain extent according to electricity price, outdoor temperature and the like under the condition of following a protocol, and interrupts short-time power supply to a pre-designated load without affecting normal work and life, such as air conditioner, large-scale industrial users and the like; b) The transferable load is a load which can delay the starting time and maintain the shape of the load curve unchanged according to the implementation electricity price and the like, such as an electric automobile power exchange station, part of resident loads and the like. The energy storage is like a high-capacity 'charge pal', and is used as a load for charging when electricity is used in low-peak and is used as a power supply for releasing electric energy when electricity is used in high-peak. The system has the characteristics of rapid, stable and accurate charge and discharge regulation, and can provide various services such as peak regulation, frequency modulation, standby, demand response and the like for a power grid.
The active and reactive power coordination loss reduction control method considering the source network load storage comprises the following steps:
step 1, establishing a new energy source access power grid system to be optimized, wherein basic parameters of the system comprise node injection power, branch parameters, initial transformer ratio, wind power output curve and photovoltaic output curve; the branch parameters comprise branch resistance, reactance and contrast sodium;
specifically, the objective function of the active-reactive coordination multi-objective optimization model is as follows:
in the above, N L And N T Respectively representing the number of branches and transformers, T is the scheduling total time period, the whole day is divided into 24 time periods, deltaT is the time length of each time period, and P Loss (l, t) is the loss of the branch l or the transformer at the time t,
r l +jx l for the impedance of branch l, P iw,t The wind power injection power of the node i at the time t is represented; p (P) iv,t Represents the photovoltaic injection power, +.>
Load power representing an unregulated load connected to node i, < >>
Load power, U, representing the adjustable load connected to node i i,t For the voltage amplitude of node i of period t, U ei Rated voltage of the node i;
the constraint conditions of the active and reactive coordination multi-objective optimization model comprise:
power balance constraint and power flow constraint:
in the above, P i,t 、Q i,t Active power and reactive power at node i at time t respectively,
active power and reactive power of conventional load of node i at t moment, P RE,i,t 、Q RE,i,t Active power and reactive power of wind power and photovoltaic injection node i at t moment respectively, +.>
Active power, reactive power and Q of i node adjustable load at t moment C,i,t Representing reactive power provided by a reactive compensation device at a node i at a moment t, and P LOSS,i,t Representing the network loss of node i at time t, P ESS,i,t Representing the active power stored by the node i at the moment t;
in the above, U i,t 、U j,t Representing the voltage magnitudes of i node and j node in the system, θ ij 、G ij 、B ij Respectively representing phase angle difference, conductance and susceptance between the node i and the node j;
the expression of the inequality constraint is:
in the above, N g U, which is the number of generators in the system i,max 、U i,min P is the upper and lower limit value of the generator terminal voltage gi,max 、P gi,min The upper limit value and the lower limit value of the active output of the generator are used; q (Q) gi,max 、Q gi,min The upper limit value and the lower limit value of reactive output of the generator are used;
the upper limit and the lower limit of the voltage of the node i are respectively;
reactive compensation constraint conditions:
in the above, Q Ci,min 、Q Ci,max Respectively represents the minimum and maximum values of the switching capacity of the reactive compensation device, T ki,min 、T ki,max Respectively representing minimum and maximum reactive power of gears of on-load voltage-regulating transformer, S C 、S k Respectively a node set where the switchable capacitor and the on-load voltage regulating transformer are located;
power supply output constraint:
in the above-mentioned method, the step of,
for the t period of time photoelectric maximumGenerating power; />
For t period of photoelectric output, < >>
Maximum power generation output of the wind power in the t period; />
Wind power output is t time period;
constraint conditions of the energy storage system:
in the above, SOC 0 For storing the SOC value at the initial moment, P ch 、P dis The charge and discharge power between t and t-1 time periods respectively is at most 0, eta ch And eta dis Respectively charge and discharge efficiency, delta t is a continuous time period of charge and discharge, S rate Is the rated capacity of energy storage;
state of charge upper and lower limit constraints:
SOC ESSi,min ≤SOC ESSi (t)≤SOC ESSi,max (8)；
in the above, SOC ESSi,min And SOC (System on chip) ESSi,max Respectively the minimum value and the maximum value allowed by the ith energy storage SOC;
energy storage charge-discharge power constraint:
in the above, P ch,max And P dis,max Respectively storing energy of the maximum charging power and the maximum discharging power;
constraints on interruptible load:
in the above-mentioned method, the step of,
to the maximum and minimum interrupt capacity of interruptible load, P IL,i,t The interrupt capacity of the ith interruptible load at the T moment, T IL,i Interrupt time for the ith interruptible load user, < +.>
Minimum and maximum interrupt time for the ith interruptible load user, N IL,i For the number of interruptions of the ith interruptible user, < >>
The maximum interruption times of the ith interruption user;
constraint that load can be transferred:
in the above, P trl (t)、P trb (t) upper and lower total transferable loads, respectively;
the total transferable loads before and after the transfer at the moment t are respectively; />
Respectively the upper limit and the lower limit of the transferable load and the transferable time range, M tr,i 、M tr,i The transferable load transfer amount and the capacity, respectively.
the specific process is as follows: firstly inputting basic parameters of a system, setting basic parameters and maximum iteration times of a particle swarm algorithm, and randomly initializing the speed and the position of particles according to the particle swarm algorithm;
the invention comprehensively considers the influence of two targets of network loss and voltage deviation on optimization, and the established weight multi-target optimization model is as follows:
F＝min(μ 1 a 1 F 1 +μ 2 a 2 F 2 ) (12)；
in the above formula: mu 1, mu 2 and mu 3 are the order coefficients; a1, a2, a3 are weight coefficients, and the equation a1+a2+a3=1 is satisfied.
The active and reactive coordination multi-objective optimization model is solved based on the weight multi-objective optimization model, so that the optimization results can be more approximate to the optimal, and the generator terminal voltage, transformer transformation ratio, reactive compensation device switching capacity, energy storage system charging and discharging strategy and flexible load investment of the system are adjusted based on the optimization results, so that active and reactive coordination loss reduction control of new energy access to the power grid is realized.
Active and reactive power coordination loss reduction control device considering source network load storage comprises:
the system comprises a parameter acquisition module, a power generation module and a photovoltaic output module, wherein the parameter acquisition module is used for establishing a new energy source to be connected into a system to be optimized of a power grid, and basic parameters of the system comprise node injection power, branch parameters, an initial transformer ratio, a wind power output curve and a photovoltaic output curve;
the model building module is used for building an active reactive power coordination multi-objective optimization model with minimum system operation network loss and voltage offset according to the system basic parameters;
the solution control module is used for solving the active and reactive coordination multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal solution set;
and the variable control module is used for adjusting the control variable of the system based on the Pareto optimal solution set, and realizing active and reactive power coordination loss reduction control of the new energy access to the power grid.
By the method, the active and reactive power coordination loss reduction control method considering the source network load storage establishes an active and reactive power coordination multi-objective optimization model with minimum system operation network loss and voltage offset on the basis of a typical wind power and photovoltaic sunrise force curve, fully considers the improvement effect of an energy storage system on the power grid voltage and network loss, can smooth the fluctuation of new energy output, and improves the level of absorption; in the multi-objective optimization problem treatment, a pareto optimal solution set is generated after optimizing, so that more optimization schemes can be provided, and the actual transformer transformation ratio, reactive compensation capacity, charging and discharging strategies of an energy storage system and flexible load are regulated and controlled, so that the effects of reducing network loss and improving voltage are achieved; specifically, parameters of energy storage and adjustable load are selected, an active and reactive coordination optimization model is established based on the parameters, transformer transformation ratio and reactive compensation capacity are used as control quantities in the reactive aspect, charge and discharge of an energy storage system and use of flexible load are used as control quantities in the active aspect, and active resources and reactive resources in the combined system can smooth new energy output, improve voltage level and reduce power grid loss.
In the embodiment, an improved IEEE-30 node system is adopted for carrying out example analysis, specific data is referred to in the website http:// www.pserc.cornell.edu/matpower, and the topology structure of the system is shown in figure 2; the reference power of the system is 100MVA, and the voltage reference value is 1.0. In an original system, nodes 7, 21 and 30 are respectively connected with wind power WT, photovoltaic PV1 and photovoltaic PV2 with installed capacities of 8 MW; the node 17 is connected with an energy storage system ESS with the capacity of 50MW, wherein the charging and discharging efficiency is 0.95, the single maximum charging and discharging power Pee is 8MW, the positive value is charging, the negative value is discharging, and the change range of the state of charge SOC of the energy storage system is 0.1-1.0p.u.; the adjustable load is connected at 22 and 23; the voltage regulating transformers are respectively arranged in four lines of 6-9, 6-10, 4-12 and 27-28, 8 gears are arranged in total, and the regulating step length is 0.025p.u.; respectively connecting 5 groups of parallel capacitors at the nodes 10 and 24, wherein the capacity of each group is 1Mvar; and the nodes 6, 20 and 29 are respectively connected with a static reactive power compensation device with the capacity of 10 Mvar.
From the pareto optimal solution set after the solution of fig. 3, it can be seen that the front surface is unfolded along a certain curve in a feasible solution area, so that the convergence is good, and a proper compromise solution is selected from the optimal solution set to be an optimal solution; as can be seen from fig. 4, the effect of reducing the loss after optimization is remarkable.
As can be derived from the load curves before and after optimization for each period of the day in fig. 5, the load can be cut off at night 22:00 does not participate in grid regulation, 24: the input amount of 00 is the largest. In other periods, the optimized load is reduced on the basis of the original load, but the overall trend of the parameter is kept unchanged. The larger the load shedding value in FIG. 6 shows that the more rigid load is in the period, as can be seen from FIG. 6, the more power is used by the user in the morning of 5:00-6:00, 8:00 in the morning, 13:00 in the noon, 16:00 in the afternoon, 20:00 in the evening and 23:00 (the power output and the load cannot reach balance), and the larger the load shedding power value is; the load reduction participation degree is low in 1:00-4:00, 9:00-12:00, 14:00-15:00 and 17:00-19:00, and the system can be regulated to reach balance.
Fig. 7 mitigates fluctuations in new energy output by adjusting the energy storage action. The wind-solar energy output characteristics are combined to be easy to analyze, so that the new energy output is larger in daytime from 7:00 to 16:00, the power grid load absorption capacity is insufficient, the energy storage system plays a role of load, excess energy emitted by a power supply is absorbed to the power grid to improve the wind-solar energy absorption capacity, the wind-solar energy waste quantity is reduced, the wind-solar energy output is smoothed, and the state of charge curve is in an ascending trend. The new energy output is reduced from afternoon to night, namely 16:00-7:00, the conventional unit output cannot meet the load demand, at the moment, the energy storage system has the function of discharging to the power grid by the power supply, the power is prevented from being transmitted remotely, the pressure of the power grid is relieved, and at the moment, the state of charge curve is in a descending trend.
Claims (6)
1. The active and reactive power coordination loss reduction control method considering the source network load storage is characterized by comprising the following steps of:
step 1, establishing a new energy source access power grid system to be optimized, wherein basic parameters of the system comprise node injection power, branch parameters, initial transformer ratio, wind power output curve and photovoltaic output curve;
step 2, according to the basic parameters of the system, an active reactive power coordination multi-objective optimization model with minimum system operation network loss and voltage offset is established;
step 3, solving the active and reactive coordination multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal solution set;
and 4, adjusting control variables of the system based on the Pareto optimal solution set, and realizing active and reactive power coordination loss reduction control of the new energy access power grid.
2. The active-reactive power coordination loss reduction control method considering source network load storage according to claim 1, wherein the objective function of the active-reactive power coordination multi-objective optimization model is as follows:
in the above, N L And N T Respectively representing the number of branches and transformers, T is the scheduling total time period, deltaT is the time length of each time period, and P Loss (l, t) is the loss of branch l or transformer at t time, g l ＝r l /(r 2 l +x 2 l )，r l +jx l For the impedance of branch l, P iw,t Represents the wind power injection power of the node i at the time t, P iv,t Represents the photovoltaic injection power of node i at time t,
load power representing an unregulated load connected to node i, < >>
Load power, U, representing the adjustable load connected to node i i,t For the voltage amplitude of node i of period t, U ei Is the rated voltage of node i.
3. The active-reactive power coordination loss reduction control method considering source network load storage according to claim 2, wherein the constraint conditions of the active-reactive power coordination multi-objective optimization model comprise a power balance constraint condition, a power flow constraint condition, a reactive power compensation constraint condition, a power source output constraint, an energy storage system constraint condition, a constraint condition capable of interrupting a load and a constraint condition capable of transferring the load.
4. The active-reactive coordination loss reduction control method considering source network load storage according to claim 3, wherein the constraint conditions of the active-reactive coordination multi-objective optimization model are as follows:
power balance constraint:
in the above, P i,t 、Q i,t Active power and reactive power at node i at time t respectively,
active power and reactive power of conventional load of node i at t moment, P RE,i,t 、Q RE,i,t Active power and reactive power of wind power and photovoltaic injection node i at t moment respectively, +.>
Active power, reactive power and Q of i node adjustable load at t moment C,i,t Representing reactive power provided by a reactive compensation device at a node i at a moment t, and P LOSS,i,t Representing the network loss of node i at time t, P ESS,i,t Representing the active power stored by the node i at the moment t;
load flow constraint conditions:
in the above, U i,t 、U j,t Representing the voltage magnitudes of i node and j node in the system, θ ij 、G ij 、B ij Respectively representing phase angle difference, conductance and susceptance between the node i and the node j;
expression of inequality constraint:
in the above, N g U, which is the number of generators in the system i,max 、U i,min P is the upper and lower limit value of the generator terminal voltage gi,max 、P gi,min The upper limit value and the lower limit value of the active output of the generator are used; q (Q) gi,max 、Q gi,min The upper limit value and the lower limit value of reactive output of the generator are used;
the upper limit and the lower limit of the voltage of the node i are respectively;
reactive compensation constraint conditions:
in the above, Q Ci,min 、Q Ci,max Respectively represents the minimum and maximum switching capacity of the reactive compensation device, T ki,min 、T ki,max Respectively representing minimum and maximum reactive power of gears of on-load voltage-regulating transformer, S C 、S k Respectively a node set where the switchable capacitor and the on-load voltage regulating transformer are located;
power supply output constraint conditions:
in the above-mentioned method, the step of,
the maximum power generation output is the photoelectric power in the t period; />
For t period of photoelectric output, < >>
Maximum power generation output of the wind power in the t period; />
Wind power output is t time period;
constraint conditions of the energy storage system:
in the above, SOC 0 For storing the SOC value at the initial moment, P ch 、P dis The charge and discharge power between t and t-1 time periods respectively is at most 0, eta ch And eta dis Respectively charge and discharge efficiency, delta t is a continuous time period of charge and discharge, S rate Is the rated capacity of energy storage;
state of charge upper and lower limit constraints:
SOC ESSi,min ≤SOC ESSi (t)≤SOC ESSi,max (8)；
in the above, SOC ESSi,min And SOC (System on chip) ESSi,max Respectively the minimum value and the maximum value allowed by the ith energy storage SOC;
upper and lower limit constraint of energy storage charging and discharging power:
in the above, P ch,max And P dis,max Respectively storing energy of the maximum charging power and the maximum discharging power;
constraints on interruptible load:
in the above-mentioned method, the step of,
to the maximum and minimum interrupt capacity of interruptible load, P IL,i,t The interrupt capacity of the ith interruptible load at the T moment, T IL,i Interrupt time for the ith interruptible load user, < +.>
Minimum and maximum interrupt time for the ith interruptible load user, N IL,i For the number of interruptions of the ith interruptible user, < >>
The maximum interruption times of the ith interruption user;
constraint that load can be transferred:
in the above, P trl (t)、P trb (t) the upper and lower limits of the total transferable loads,
the total transferable loads before and after the transfer at the moment t are respectively; />
Respectively the upper limit and the lower limit of the transferable load and the transferable time range, M tr,i 、M tr,i The transferable load transfer amount and the capacity, respectively.
5. The active-reactive power coordinated loss reduction control method considering source network load storage according to claim 1, wherein the control variables in the step 4 include generator terminal voltage, transformer transformation ratio, reactive power compensation device switching capacity, energy storage system charging and discharging strategy and input of flexible load.
6. Active and reactive power coordination loss reduction control device considering source network load storage is characterized by comprising:
the system comprises a parameter acquisition module, a power generation module and a photovoltaic output module, wherein the parameter acquisition module is used for establishing a new energy source to be connected into a system to be optimized of a power grid, and basic parameters of the system comprise node injection power, branch parameters, an initial transformer ratio, a wind power output curve and a photovoltaic output curve;
the model building module is used for building an active reactive power coordination multi-objective optimization model with minimum system operation network loss and voltage offset according to the system basic parameters;
the solution control module is used for solving the active and reactive coordination multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal solution set;
and the variable control module is used for adjusting the control variable of the system based on the Pareto optimal solution set, and realizing active and reactive power coordination loss reduction control of the new energy access to the power grid.
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