A method for reactive power optimization and voltage control of power grid based on gravity energy storage

Abstract

The application relates to a power grid reactive power optimization and voltage control method based on gravity energy storage, relates to a power grid reactive power optimization and voltage control technology, and aims to solve the voltage instability problem of a power grid node after a high proportion of renewable energy is connected to a power system. When voltage fluctuation occurs in the power grid system, a primary population is generated by using a voltage wave; the voltage fluctuation result of the power grid system is determined through power flow calculation; whether the voltage fluctuation result meets the operation condition of the power grid system is judged; if not, the primary population is regenerated; if the operation condition of the power grid system is met, the particle speed and the global optimal position are solved through power flow calculation, and are updated; whether the particle speed and the global optimal position after the update meet the energy storage constraint condition is judged; if not, power flow calculation is performed again; if the energy storage constraint condition is met, the voltage fluctuation result of the power grid system is output. The beneficial effect is that the voltage stability of the power grid node is good.

Description

Technical Field

[0001] This invention relates to a power grid reactive power optimization and voltage control technology. Background Technology

[0002] With the continuous increase in the proportion of new energy sources, the entire power system will face significant changes and challenges. Due to the randomness and intermittency of renewable energy sources such as wind and solar power, large-scale grid connection of renewable energy will inevitably affect the grid's dispatch and control. However, energy storage can fundamentally solve the problems of stable operation and reliable power supply brought about by new energy sources. Currently, there are many relatively mature energy storage technologies, such as pumped hydro storage, battery energy storage, and flywheel energy storage. Meanwhile, gravity energy storage is a system that relies on gravitational potential energy for energy storage. Compared with pumped hydro storage and battery energy storage, it has certain advantages in adapting to different geographical environments and temperature conditions, and has good application prospects. To adapt to the increasingly diversified new energy power generation systems, future energy storage systems will inevitably develop towards a multi-type, distributed approach. However, with the rapid increase in the number and capacity of grid-connected energy storage systems, the management difficulty and complexity of regional power grids that include wind-solar-storage combined power generation systems are constantly increasing. Moreover, after the installed capacity of energy storage reaches a certain scale, the coordinated control of energy storage by the regional power grid becomes more difficult, with reactive power and voltage issues being the most prominent problems. The large-scale grid connection of new energy sources has squeezed out power generation space, leading to a decrease in the proportion of thermal power units and insufficient reliable reactive power sources to maintain grid voltage stability. Therefore, more reactive power compensation technologies and equipment suitable for the new grid configuration are needed.

[0003] To address the voltage control problem in new power grids, research has been conducted on the reactive power regulation capability of photovoltaic inverters, establishing a multi-mode voltage control model for low-voltage distribution networks. A zoned voltage control strategy based on static synchronous compensators (SSCs) has been proposed for voltage control in distribution networks. Energy storage devices have been used to suppress the impact of active power output fluctuations of photovoltaic systems on grid voltage stability. However, none of these studies have considered the role of energy storage systems in voltage control. Regarding the coordinated operation and stable voltage control of energy storage, voltage control has been implemented for grid-connected wind farms, with the established model taking into account the spatiotemporal distribution characteristics of reactive power. For grid-connected photovoltaic-storage microgrids, a power capacity optimization configuration model has been established with the goal of minimizing levelized cost of electricity (LCOE). Energy storage is used to regulate the active and reactive power of active distribution networks, and coordinated operation optimizes the frequency and voltage stability of the control system, mitigating system voltage fluctuations. A voltage control strategy for active distribution networks has been established using multi-agent theory, which, based on distributed computing, achieves optimal voltage at each node in the network while maximizing the absorption rate of renewable energy. However, these studies have not explored gravity energy storage in great depth. Summary of the Invention

[0004] The purpose of this invention is to solve the problem of voltage instability at grid nodes after a high proportion of renewable energy is integrated into the power system, and to propose a grid reactive power optimization and voltage control method based on gravity energy storage.

[0005] The power grid reactive power optimization and voltage control method based on gravity energy storage described in this invention includes the following steps:

[0006] Step 1: Determine if there are voltage fluctuations in the power grid system. If there are voltage fluctuations, proceed to Step 2; otherwise, proceed to Step 9.

[0007] Step 2: Initialize the voltage fluctuations of the power grid system as the original population to generate the first generation population;

[0008] Step 3: Perform power flow calculations on the initial population generated in Step 2 to determine the voltage fluctuation results of the power grid system;

[0009] Step 4: Based on the stability of the power grid system, determine whether the voltage fluctuation result of the power grid system determined in Step 3 meets the operating conditions of the power grid system; if it meets the operating conditions of the power grid system, proceed to Step 5; otherwise, return to Step 2.

[0010] Step 5: Calculate the switching power of gravity energy storage in the power grid system;

[0011] Step 6: Based on the switching power of gravity energy storage in the power grid system calculated in Step 5, solve for the particle velocity and the global optimal position;

[0012] Step 7: Update the particle velocity and global optimal position obtained in Step 6;

[0013] Step 8: Determine whether the updated particle velocity and global optimal position satisfy the energy storage constraint; if they satisfy the energy storage constraint, proceed to Step 9; otherwise, return to Step 3.

[0014] Step 9: Output the voltage fluctuation results of the power grid system.

[0015] The beneficial effects of this invention are: the voltage control method uses power flow, system operation and energy storage power as constraints, and adopts a particle swarm optimization algorithm based on a competition mechanism to solve the problem; it effectively solves the problem of voltage instability at grid nodes after a high proportion of renewable energy is connected to the power system. Attached Figure Description

[0016] Figure 1 The flowchart is a power grid reactive power optimization and voltage control method based on gravity energy storage as described in Specific Implementation 1.

[0017] Figure 2This is a schematic diagram of the gravity energy storage converter structure model in Specific Implementation Method 1;

[0018] Figure 3 This is a schematic diagram of a typical vector state of the gravity energy storage converter in Specific Implementation Method 1;

[0019] Figure 4 This is a schematic diagram of a typical topology of the gravity energy storage converter in Specific Implementation Method 1;

[0020] Figure 5 This is a schematic diagram of the gravity energy storage energy conversion process in Specific Implementation Method 1;

[0021] Figure 6 This is a schematic diagram of the topology of a 50-node system in a certain region in Specific Implementation Method 1. Detailed Implementation

[0022] Specific implementation method one: Combining Figures 1 to 6 This embodiment describes a power grid reactive power optimization and voltage control method based on gravity energy storage, which includes the following steps:

[0023] Step 1: Determine if there are voltage fluctuations in the power grid system. If there are voltage fluctuations, proceed to Step 2; otherwise, proceed to Step 9.

[0024] Step 2: Initialize the voltage fluctuations of the power grid system as the original population to generate the first generation population;

[0025] Step 3: Perform power flow calculations on the initial population generated in Step 2 to determine the voltage fluctuation results of the power grid system;

[0026] Step 4: Based on the stability of the power grid system, determine whether the voltage fluctuation result of the power grid system determined in Step 3 meets the operating conditions of the power grid system; if it meets the operating conditions of the power grid system, proceed to Step 5; otherwise, return to Step 2.

[0027] Step 5: Calculate the switching power of gravity energy storage in the power grid system;

[0028] Step 6: Based on the switching power of gravity energy storage in the power grid system calculated in Step 5, solve for the particle velocity and the global optimal position;

[0029] Step 7: Update the particle velocity and global optimal position obtained in Step 6;

[0030] Step 8: Determine whether the updated particle velocity and global optimal position satisfy the energy storage constraint; if they satisfy the energy storage constraint, proceed to Step 9; otherwise, return to Step 3.

[0031] Step 9: Output the voltage fluctuation results of the power grid system.

[0032] In this embodiment, the reactive power compensation principle of gravity energy storage is realized based on the energy storage converter and the gravity energy storage power model;

[0033] The Power Converter System (PCS) is a key component of gravity energy storage systems. The energy storage system interacts with the grid through power electronic devices within the PCS. By controlling the amplitude of the PCS output voltage and the angle between it and the grid voltage vector, the phase difference between the grid voltage and the converter output current, as well as the magnitude of the output current, can be adjusted. This allows the PCS to operate in four quadrants, generating and absorbing reactive power while simultaneously controlling the transfer of active and reactive power on both the AC and DC sides. A specific gravity energy storage PCS is shown below. Figure 2 The structure is shown, where E AC E DC These are the AC-side electromotive force of the power grid and the DC-side electromotive force of the energy storage, respectively; U AC U DC These are the AC input voltage and the DC bus voltage, respectively; I AC I DC These are the AC current on the grid side and the DC current on the energy storage side, respectively; X AC R is the equivalent reactance on the grid side; DC The equivalent resistance of the energy storage side; by Figure 2 It can be seen that when the grid-side electromotive force E AC When used as a reference quantity, the AC voltage vector U is changed. AC Control grid-side current vector I AC EMF on the grid side AC With current I AC When the phase difference changes, the energy storage converter can exchange active and reactive power with the power grid to achieve reactive power compensation. Figure 3 The vector states represent the four typical operating modes of the gravity energy storage converter; Figure 3 Middle,U X =I AC ×X AC This refers to the voltage drop generated by the equivalent reactance on the grid side; the energy storage converter, as a reactive power generating device in a gravity energy storage system, has a topology divided into single-stage (DC / AC type) and two-stage (DC / DC-DC / AC type), and its typical topology is as follows: Figure 4 As shown; the single-stage energy storage converter has the advantages of simple structure and easy control; the energy storage converter connects the gravity energy storage system to the power grid through the converter circuit and the filter circuit. By sampling the AC side voltage and current values ​​of the converter, and through the coordinate transformation stage, the control stage, and the waveform modulation stage, the switching devices are controlled to achieve reactive power control.

[0034] For the gravity energy storage power model, energy is stored using the height difference. When electricity is abundant, the motor operates electrically, drawing power from the grid to lift the object to a certain height, completing the energy conversion from electrical energy to gravitational potential energy, storing electrical energy in the form of gravitational potential energy. When electricity is scarce, the object is released, driving the motor to operate in a generator-like manner, feeding electricity back to the grid, completing the energy conversion from gravitational potential energy to electrical energy. The energy conversion process of gravity energy storage is as follows: Figure 5 As shown.

[0035] In this embodiment, a 50-node system of a regional power grid is used for reactive power optimization and voltage control simulation calculations. The example topology is as follows: Figure 6 As shown, the area includes 5 500kV substations, 26 220kV substations, 3 220kV switching stations, and 5 220kV high-speed rail traction substations; 5 thermal power plants (two of which are 500kV), 2 hydropower plants, and 4 wind farms; 6 500kV transmission lines and 56 220kV transmission lines. The load level is selected during the peak winter load period, when voltage levels at each station are generally low. This example constructs three scenarios to analyze the impact of reactive power optimization of gravity energy storage on voltage.

[0036] (1) Case 1: No control measures are used for reactive power optimization, which is used as the basic example;

[0037] (2) Case 2: Reactive power optimization is performed using on-load tap-changing transformers and capacitors. The decision variables are the tap position of the transformer and the switching capacity of the capacitor.

[0038] (3) Case 3: All equipment participates in reactive power optimization. In addition to the transformer tapping situation and capacitor switching capacity in Example 2, the decision variables also include the charging and discharging power of the gravity energy storage system.

[0039] Table 1 shows the voltage control of each major node under three different conditions.

[0040] Table 1. Voltage control status of key nodes under three conditions (unit: kV)

[0041]

[0042]

[0043] The optimization results in Table 1 show that simply using on-load tap-changing transformers and capacitors for reactive power optimization improved the voltage situation at each node, but the results were uneven. For example, the optimized voltages at nodes 4, 6, 8, 19, and 20 were slightly higher, with the highest voltage at node 6 exceeding the reference voltage by 7.60%. However, the voltages at nodes 37-43 remained low, with the lowest being 4.09% below the reference voltage. In case 3, after incorporating particle swarm gravity energy storage reactive power optimization and voltage control strategies, the voltages at each node were not only improved but also relatively balanced, with voltage deviations controlled between -0.45% and 5.2%. This indicates that the gravity energy storage system played a positive role in improving the grid voltage.

[0044] Specific Implementation Method Two: This implementation method further defines the power grid reactive power optimization and voltage control method based on gravity energy storage described in Specific Implementation Method One. In this implementation method, the specific method for determining the voltage fluctuation result of the power grid system in step three is as follows:

[0045] Under the premise that the power grid satisfies active power balance and reactive power balance at any time, the voltage fluctuation result of the power grid system is obtained by formula (1); the specific formula (1) is:

[0046]

[0047] Where ΔU represents voltage fluctuation; T represents calculation time; U n,t U is the voltage at node n during time interval t; n ′ ,t U is the reference voltage at node n during time period t; n,min U is the minimum allowable voltage at node n during time period t. n,max The maximum allowable voltage at node n during time period t;

[0048] The power grid satisfies active power balance and reactive power balance at any given time, as expressed by formulas (2) and (3); specifically, formulas (2) and (3) are:

[0049]

[0050]

[0051] Among them, P n,G Q represents the active power emitted by node n; n,G P represents the reactive power emitted by node n; n,L Q represents the active load of node n; n,L R represents the reactive load of node n; l X is the resistance value of branch l; l P is the reactance value of branch l; lQ represents the active power transmitted on branch l. l U represents the reactive power transmitted on branch l. l Let be the voltage value of branch l.

[0052] Specific Implementation Method Three: This implementation method further defines the power grid reactive power optimization and voltage control method based on gravity energy storage described in Specific Implementation Method One. In this implementation method, the operating condition of the power grid system in step four is: the branch current amplitude is less than or equal to the upper limit of the current amplitude in time period t; that is...

[0053] I l,t ≤I l,max (4)

[0054] Among them, I l,t Let I be the amplitude of the branch current during the time interval t. l,max This represents the upper limit of the current amplitude during the time period t;

[0055] Simultaneously, the voltage of node n during time period t is greater than or equal to the lower limit of the voltage of node n during time period t, and less than or equal to the upper limit of the voltage of node n during time period t; that is...

[0056] U n,min ≤U n,t ≤U n,max (5)

[0057] Among them, U n,t U is the voltage at node n during time interval t; n,min U is the minimum allowable voltage at node n during time period t. n,max Let n be the maximum allowable voltage at node n during time period t.

[0058] Specific Implementation Method Four: This implementation method further defines the power grid reactive power optimization and voltage control method based on gravity energy storage described in Specific Implementation Method One. In this implementation method, in step six, a particle swarm optimization algorithm based on a competition mechanism is used to solve for the particle velocity and the global optimal position. The specific solution algorithm is expressed by formulas (6) and (7):

[0059] H i (t)=ωH i (t-1)+c1r1×[F b -B i (t-1)]+c2r2×[G b -B i (t-1)] (6)

[0060] B i (t)=B i (t-1)+H i (t) (7)

[0061] Among them, H i (t) represents the velocity of the i-th particle at time t; H i (t-1) is the velocity of the i-th particle at time t-1; ω is the inertia coefficient; c1 is the self-empirical coefficient; c2 is the social empirical coefficient; r1 is a random constant between 0 and 1; r2 is another random constant between 0 and 1; F b The optimal position in particle history; G b B represents the optimal position in the population history of particle i. i (t) represents the global optimal position of the i-th particle at time t; B i (t-1) represents the global optimal position of the i-th particle at time t-1.

[0062] In this embodiment, the algorithm helps to accelerate the convergence of the algorithm and can better guarantee the distribution of the algorithm.

[0063] Specific Implementation Method Five: This implementation method further defines the power grid reactive power optimization and voltage control method based on gravity energy storage described in Specific Implementation Method One. In this implementation method, the energy storage constraint condition in step eight is:

[0064] P G,min ≤P G,t ≤P G,max (8)

[0065] Among them, P G,t P represents the power generated by gravity-stored energy over time interval t. G,min P is the minimum power allowed to be emitted by a gravity energy storage device. G,max The maximum power that a gravity energy storage device is allowed to generate;

[0066] For different forms of gravity energy storage systems, there are:

[0067] P G,t ∈(P VG ,P SG (9)

[0068] Among them, P VG P represents the energy release power of a vertical gravity energy storage system. SG This represents the energy release power of the slope-type gravity energy storage system.

[0069] The energy release power of the vertical gravity energy storage system is calculated using formula (10);

[0070] P VG =F VG ×v VG (10)

[0071] Among them, FVG The generator traction force when releasing heavy objects from a vertical gravity energy storage system; v VG The speed at which the weight falls;

[0072] When the generator is in power generation mode, the weight should descend at a constant speed. VG This is the speed at which the weight falls vertically;

[0073] F VG We can obtain the following from formula (11):

[0074] F VG =m1g-Fμ1 (11)

[0075] Where m1 is the mass of the vertically falling object; g is the acceleration due to gravity; F μ1 Friction force in a vertical gravity energy storage system;

[0076] The energy release power of the slope-type gravity energy storage system is calculated using formula (12);

[0077] P SG =F SG ×v SG (12)

[0078] Among them, F SG The generator traction force when releasing heavy objects from a slope-type gravity energy storage system; v SG The velocity of the weight as it descends the inclined plane;

[0079] F SG It can be obtained from formula (13);

[0080] F SG =m2g×sinθ-Fμ2 (13)

[0081] Where m2 is the mass of the weight descending along the inclined plane; θ is the angle of inclination of the inclined plane; F μ2 This is the frictional force between the weight descending along the inclined plane and the inclined plane.

[0082] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for reactive power optimization and voltage control of a power grid based on gravity energy storage, the method comprising the following steps: Step one, judging whether a voltage fluctuation occurs in the power grid system, if the voltage fluctuation occurs in the power grid system, executing step two; otherwise, executing step nine; Step two, initializing the voltage fluctuation of the power grid system as an original population to generate a primary population; Step three, performing a power flow calculation on the primary population generated in step two to determine the voltage fluctuation result of the power grid system; Step four, judging whether the voltage fluctuation result of the power grid system determined in step three meets the operating condition of the power grid system on the basis of the stability of the power grid system, if the voltage fluctuation result meets the operating condition of the power grid system, executing step five; otherwise, returning to execute step two; Step five, calculating the switching power of the gravity energy storage in the power grid system; Step six, solving the velocity and global optimal position of the particle according to the switching power of the gravity energy storage in the power grid system calculated in step five; Step seven, updating the velocity and global optimal position of the particle solved in step six; Step eight, judging whether the updated velocity and global optimal position of the particle meet the energy storage constraint condition, if the velocity and global optimal position meet the energy storage constraint condition, executing step nine; otherwise, returning to step three; Step nine, outputting the voltage fluctuation result of the power grid system; The specific method for determining the voltage fluctuation result of the power grid system in step three is that the voltage fluctuation result of the power grid system is obtained from formula (1) under the premise that the power grid satisfies active power balance and reactive power balance at any time; the specific formula (1) is: The power grid satisfying active power balance and reactive power balance at any time is represented by formula (2) and formula (3); the specific formula (2) and formula (3) are: The operating condition of the power grid system in step four is that the branch current amplitude in the t time period is less than or equal to the upper limit of the current amplitude in the t time period; that is, （1） wherein, V is the voltage fluctuation; T is the calculation time; V is the voltage at node n for the time period t; V is the reference voltage at node n for the time period t; V is the minimum allowed voltage at node n for the time period t, V is the maximum allowed voltage at node n for the time period t; At the same time, the voltage of node n in the t time period is greater than or equal to the lower limit of the voltage of node n in the t time period and less than or equal to the upper limit of the voltage of node n in the t time period; that is, （2） （3） wherein, Pn represents the active power delivered by node n; Qn represents the reactive power delivered by node n; Pn represents the active load at node n; Qn represents the reactive load at node n; Rl represents the resistance value of branch l; Xl represents the reactance value of branch l; Pl represents the active power delivered by branch l; Ql represents the reactive power delivered by branch l; Vl represents the voltage value of branch l.

2. The method of claim 1, wherein, In step six, the velocity and global optimal position of the particle are solved by using a particle swarm optimization algorithm based on a competition mechanism, and the specific solving algorithm is represented by formula (6) and formula (7): The energy storage constraint condition in step eight is: （4） wherein, is the branch current amplitude for the time period t, is the upper limit of the current amplitude for the time period t. For different forms of gravity energy storage systems, there are: （5） wherein, Vn(t) is the voltage of node n at time t; Vn,min(t) is the minimum allowed voltage of node n at time t, Vn,max(t) is the maximum allowed voltage of node n at time t.

3. The method of claim 1, wherein, The discharging power of the vertical gravity energy storage system is calculated by formula (10); （6） （7） wherein, is the velocity of the i-th particle at time t; is the velocity of the i-th particle at time t-1; is the velocity of the i-th particle at time t; is the velocity of the i-th particle at time t-1; is the inertia coefficient; is the self-experience coefficient; is the social-experience coefficient; is a random constant between 0 and 1; is another random constant between 0 and 1; is the particle's historical best position; is the swarm's historical best position for particle i; is the global best position of the i-th particle at time t; is the global best position of the i-th particle at time t-1; is the global best position of the i-th particle at time t; is the global best position of the i-th particle at time t-1.

4. The method of claim 1, wherein, The discharging power of the slope gravity energy storage system is calculated by formula (12); （8） wherein, Pgravtis the power emitted by the gravitational energy storage for a time period t; Pgravmin the minimum power allowed to be emitted by the gravitational energy storage; Pgravmax the maximum power allowed to be emitted by the gravitational energy storage; ​ （9） wherein, is the discharging power of a vertical gravity energy storage system; is the discharging power of a slope gravity energy storage system; ​ （10） wherein, is the generator pull force when releasing the weight for a vertical gravity energy storage system; is the weight descent speed; When the generator is in the power generation state, the weight should keep uniform speed to drop, That is, the vertical dropping speed of the weight; From equation (11) we obtain: （11） wherein, is the mass of the vertically descending weight; is the acceleration due to gravity; is the friction of the vertical gravity energy storage system; ​ （12） wherein, is the generator pull force when releasing the weight of the ramped gravity energy storage system; is the speed of the weight down the ramp. is obtained from equation (13); （13） wherein, is the mass of the weight descending the ramp; is the angle of inclination of the ramp; is the friction between the weight descending the ramp and the ramp.

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