Mobile energy storage and power dispatching optimization method in micro-grid

Abstract

The invention relates to the technical field of control algorithm design of a new energy power generation system, in particular to a method for optimizing mobile energy storage and power dispatching in a micro-grid, which comprises the following steps of: establishing mathematical cost models of mobile energy storage and each part of the micro-grid, obtaining a multi-unit coordinated dispatching comprehensive cost minimization objective function, and designing constraint conditions; by using the mobile energy storage equipment, when extreme weather occurs or power equipment emergently breaks down, the minimum economic cost is taken as a target, power dispatching among units is realized, stable operation of the power distribution network is maintained, and maximization of the economic benefit of operation of the power distribution network is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of control algorithm design of a new energy power generation system, and in particular to a mobile energy storage and power dispatch optimization method in a microgrid. Background Art

[0002] Mobile energy storage technology is currently in a stage of rapid development. Globally, especially in China, which is the leader in the new energy market, the demand for mobile energy storage market continues to expand. This is due to the rapid growth of renewable energy, the increase in grid peak load demand, and the rising demand for emergency power solutions. Market research reports show that the mobile energy storage market is developing steadily, and the supply market has formed a certain basic layout. Mobile energy storage is not only limited to the traditional power system support and emergency power supply fields, but also penetrates into more diversified scenarios, including outdoor activity power supply, energy supply in remote areas, capacity expansion of electric vehicle charging stations, and integrated application with renewable energy power generation facilities.

[0003] At present, mobile energy storage technologies include many types, such as lithium-ion batteries, flywheel energy storage, supercapacitors, etc. Among them, lithium-ion batteries have become the mainstream due to their high energy density and long cycle life. Continuous technological progress has improved energy storage efficiency and gradually reduced costs, which has promoted the expansion of the market.

[0004] The mobile energy storage industry still faces challenges such as cost control, safety improvement, standardization, and insufficient consumer awareness. The industry is actively exploring solutions, such as reducing costs through technological innovation, strengthening safety standards and testing, and raising consumers' awareness of the value of mobile energy storage through market education.

[0005] Microgrids include traditional power generation units such as diesel generators, new energy generation (wind power generation, photovoltaic power generation), local loads, etc. In microgrids that include new energy generation, fixed energy storage devices are usually equipped to maintain power balance within and between grids. However, when emergency deployment is required in the face of extreme weather or power equipment failure, mobile energy storage devices can well meet this demand. Summary of the invention

[0006] In view of this, the purpose of the present invention is to propose a mobile energy storage and power dispatch optimization method in a microgrid to solve the problem of optimizing the dispatch of mobile energy storage equipment when emergency deployment is required due to extreme weather or power equipment failure.

[0007] Based on the above purpose, the present invention provides a method for optimizing mobile energy storage and power dispatch in a microgrid, comprising the following steps:

[0008] S1. Establish mathematical cost models for mobile energy storage and microgrid components;

[0009] S2. Based on the mathematical cost model in S1, establish the objective function of minimizing the comprehensive cost of multi-unit coordinated scheduling;

[0010] S3, establish the constraints for minimizing the objective function;

[0011] S4. With the minimum economic cost as the goal, the power dispatch of each unit is achieved by minimizing the objective function and constraints.

[0012] Preferably, each part of the mathematical cost model includes a diesel generator cost model, a wind power generation and photovoltaic power generation economic cost model, and a mobile energy storage cost model.

[0013] Preferably, the diesel generator cost model is C DG =C DG_fu +C DG_main ;

[0014]

[0015] C DG_main =a DG ×P DG ;

[0016] Among them, C DG is the diesel generator cost, c DG is the diesel price per unit power, P DG is the power generated by the diesel generator per hour, C DG_main is the labor maintenance cost of diesel generator, a DG is the diesel generator maintenance cost coefficient, C DG_fu It is the fuel cost per hour for diesel generator.

[0017] Preferably, the economic cost model of wind power generation and photovoltaic power generation is:

[0018] C WT =c WT ·P WT +λP WT -P WTN |·u(t)+a WT ·P WT ;

[0019] C PV =c PV ·P PV +λP PV -P PVN |·u(t)+a PV ·P PV ;

[0020] Among them, C WT and C PVare the cost models for wind power generation and photovoltaic power generation, c WT and c PV are the electricity price cost per unit power, P WT is the actual output power of the fan, P PV is the actual output power of photovoltaic power, λ is the penalty rate, a WT and a PV are the maintenance cost coefficients of wind power generation and photovoltaic power generation equipment respectively, u(t) is a defined binary variable, u(t) = {0, 1}, when the output power of the wind turbine and photovoltaic array is less than the rated value, u(t) = 0 at this moment, and when it is greater than the rated value, u(t) = 1 at this moment.

[0021] Preferably, the calculation model of the actual output power of the wind turbine and the actual output power of the photovoltaic power is:

[0022]

[0023] In the formula, v ci 、v N 、v co are cut-in, rated and cut-out wind speeds respectively, a and b are conversion coefficients, P WTN is the rated output power of the fan;

[0024]

[0025] P PVN is the photovoltaic rated power, f PV is the power output efficiency, G PVN is the rated light intensity, ρ is the temperature coefficient, T and T N They are the actual surface temperature and the rated temperature respectively.

[0026] Preferably, the mobile energy storage cost model is:

[0027] C b =a b ·ζ ij +e b ·|P b |+C tra ;

[0028] Among them, C b is the mobile energy storage cost, a b is the fuel consumption per unit time, e b is the unit power aging coefficient, P b is the charging and discharging power of mobile energy storage, C tra For labor costs;

[0029]

[0030] ζ ij and lij are the time and distance taken for the mobile energy storage to be transported from the i-th microgrid to the j-th microgrid, t tra is the traffic jam time per unit distance, v ave is the average speed of the truck, T inst Install time for the device.

[0031] Preferably, in step S2, the economic cost minimization objective function minC established is:

[0032]

[0033] Where i = 1, 2, 3 ... n, represents the number of microgrids, t = 1, 2, 3 ... T represents a certain moment, C DG , C WT , C PV , C b They represent the operating cost of diesel generators, the cost of wind power generation, the cost of photovoltaic power generation and the cost of mobile energy storage respectively.

[0034] Preferably, in step S3, the constraints include:

[0035] P DG_min ≤P DG ≤P DG_max ;

[0036] P WT_min ≤P WT ≤P WT_max ;

[0037] P PV_min ≤P PV ≤P PV_max ;

[0038] P b_min ≤P b ≤P b_max ;

[0039] SOC min ≤SOC≤SOC max ;

[0040] Where P DG_min and P DG_max are the minimum and maximum power per hour of the diesel motor, P WT_min and P WT_max are the minimum and maximum output power allowed by the fan, P PV_min and P PV_max are the minimum and maximum output power allowed by the photovoltaic array, P b_min and P b_max They are the minimum or maximum charging and discharging power of mobile energy storage, SOC minand SOC max are the minimum and maximum allowable states of charge for mobile energy storage, SOC is the state of charge for energy storage, P DG , P WT , P PV , P b They are the power generated by the diesel generator per hour, the actual output power of the wind turbine, the actual output power of the photovoltaic power plant, and the charging and discharging power of the mobile energy storage.

[0041] Beneficial effects of the present invention: The present invention designs a mobile energy storage and power dispatch optimization model in a microgrid, establishes mathematical cost models of mobile energy storage and each part of the microgrid, obtains the objective function of minimizing the comprehensive cost of multi-unit coordinated dispatch, designs constraints, and utilizes mobile energy storage equipment. In the event of extreme weather or emergency failure of power equipment, with the minimum economic cost as the goal, the power dispatch between units is achieved, the stable operation of the distribution network is maintained, and the economic benefits of the distribution network operation are maximized. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 Schematic diagram of the process of the mobile energy storage and power dispatch optimization method in the microgrid according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0045] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0046] like Figure 1 As shown, the embodiment of this specification provides a method for optimizing mobile energy storage and power dispatch in a microgrid, which is specifically performed according to the following steps:

[0047] Step 1: Establish mathematical cost models for mobile energy storage and microgrid components;

[0048] Step 2: Establish the objective function of minimizing the comprehensive cost of multi-unit coordinated scheduling;

[0049] Step 3: Establish constraints.

[0050] The present invention is also characterized in that:

[0051] Step 1: Establish mathematical cost models for mobile energy storage and microgrid components;

[0052] Step 1.1 Establish diesel generator cost model

[0053] The diesel generator cost model mainly consists of unit hour fuel cost and maintenance cost. First, the diesel generator unit hour fuel cost C is established. DG_fu Cost Model:

[0054]

[0055] In the formula, c DG is the diesel price per unit power, P DG It is the power generated by the diesel generator per hour.

[0056] Secondly, establish the labor maintenance cost of diesel generator C DG_fu Model:

[0057] C DG_main =a DG ×P DG (2);

[0058] In the formula, a DG It is the maintenance cost factor of diesel generator.

[0059] From equations (1) and (2), the diesel generator operation cost model can be obtained as follows:

[0060] C DG =C DG_fu +C DG_main (3);

[0061] Step 1.2 Establish wind power generation model

[0062] Renewable energy generation is intermittent and uncertain. For wind power generation, the power generated by the wind turbine mainly depends on the wind speed, so the actual output power P of the wind turbine WTAnd the actual wind speed v can be expressed as follows:

[0063]

[0064] In the formula, v ci 、v N 、v co are cut-in, rated and cut-out wind speeds respectively, a and b are conversion coefficients, P WTN is the rated output power of the fan.

[0065] Step 1.3 Establish photovoltaic power generation model

[0066] Photovoltaic power generation is also intermittent and uncertain, mainly depending on the light intensity and temperature. The mathematical model of photovoltaic power generation is established as follows:

[0067]

[0068] Where P PV , P PVN are the actual photovoltaic output power and rated power, respectively, PV is the power output efficiency, G PV and G PVN are the actual light intensity and the rated light intensity, respectively, ρ is the temperature coefficient, T and T N They are the actual surface temperature and the rated temperature respectively.

[0069] Step 1.4 Establish economic cost model for wind power generation and photovoltaic power generation

[0070] Define binary variable u(t) = {0, 1}. When the output power of wind turbine and photovoltaic array is less than the rated value, u(t) = 0, and it can supply power to local load and transmit it to distribution network. When it is greater than the rated value, u(t) = 1, and wind and solar power are abandoned, and a certain penalty rate is imposed. Establish wind and solar power generation cost model:

[0071] C WT =c WT ·P WT +λ|P WT -P WTN |·u(t)+a WT ·P WT (6);

[0072] C PV =c PV ·P PV +λ|P PV -P PVN |·u(t)+a PV ·P PV (7);

[0073] In the formula, CWT and C PV are the cost models for wind power generation and photovoltaic power generation, c WT and c PT are the electricity price cost per unit power (the actual values ​​of the two are equal), λ is the penalty rate, and a WT and a PV are the maintenance cost coefficients of wind power generation and photovoltaic power generation equipment respectively.

[0074] Step 1.5 Establish a mobile energy storage cost model

[0075] Mobile energy storage equipment is transported to a designated location by a truck within a specified time, so mobile energy storage can move between different microgrids, and there are changes in space and time, that is, there are spatiotemporal characteristics. The change of the spatial position of mobile energy storage mainly depends on the change of time. There are three important indicators: traffic congestion time, average normal travel time and energy storage equipment installation time. Therefore, a mathematical model of mobile energy storage transportation time is established:

[0076]

[0077] In the formula, ζ ij and l ij are the time and distance taken for the mobile energy storage to be transported from the i-th microgrid to the j-th microgrid, t tra is the traffic jam time per unit distance, v ave is the average speed of the truck, T inst Install time for the device.

[0078] Considering the aging loss and labor cost of mobile energy storage, the mobile energy storage cost model C can be established. b :

[0079] C b =a b ·ζ ij +e b ·|P b |+C tra (9);

[0080] In the formula, a b is the fuel consumption per unit time, e b is the unit power aging coefficient, P b is the charging and discharging power of mobile energy storage, C tra For labor costs.

[0081] Step 2: Establish the objective function of minimizing the comprehensive cost of multi-unit coordinated scheduling;

[0082] Combined with the cost models in step 1, the economic cost minimization objective function minC is established:

[0083]

[0084] In the formula, i = 1, 2, 3...n, represents the number of microgrids, and t = 1, 2, 3...T represents a certain moment.

[0085] Step 3: Establish constraints.

[0086] Establish constraint models for each part separately:

[0087] P DG_min ≤P DG ≤P DG_max (11);

[0088] P WT_min ≤P WT ≤P WT_max (12);

[0089] P PV_min ≤P PV ≤P PV_max (13);

[0090] P b_min ≤P b ≤P b_max (14);

[0091] SOC min ≤SOC≤SOC max (15);

[0092] Where P DG_min and P DG_max are the minimum and maximum power per hour of the diesel motor, P WT_min and P WT_max are the minimum and maximum output power allowed by the fan, P PV_min and P PV_max are the minimum and maximum output power allowed by the photovoltaic array, P b_min and P b_max They are the minimum or maximum charging and discharging power of mobile energy storage, SOC min and SOC max They are the minimum and maximum allowable states of charge for mobile energy storage, and SOC is the state of charge for energy storage.

[0093] Figure 1 This is a schematic diagram of the execution steps of the control algorithm of the present invention, specifically:

[0094] For the research on mobile energy storage and power dispatch optimization models in microgrids, the dispatch target is first clarified: the economic cost minimization is the control target. Secondly, according to the operating constraints, it is ensured that various indicators meet the actual standards so that feedback can be given upward to adjust the target strategy in time. Finally, according to the quantitative analysis of the calculation results, the operation rules of the distribution network are mastered and the control strategy is adjusted in time.

[0095] Those skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the present invention is limited to these examples; under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for optimizing mobile energy storage and power dispatching in a microgrid, characterized in that: The optimization method comprises the following steps: S1. Establish mathematical cost models for mobile energy storage and microgrid components; S2. Based on the mathematical cost model in S1, establish the objective function of minimizing the comprehensive cost of multi-unit coordinated scheduling; S3, establish the constraints for minimizing the objective function; S4. With the minimum economic cost as the goal, the power dispatch of each unit is achieved by minimizing the objective function and constraints.

2. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 1, characterized in that: The mathematical cost models of each part include a diesel generator cost model, a wind power generation and photovoltaic power generation economic cost model, and a mobile energy storage cost model.

3. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 2, characterized in that: The diesel generator cost model is C DG =C DG_fu +C DG_main ; C DG_main =a DG ×P DG ; Among them, C DG is the diesel generator cost, c DG is the diesel price per unit power, P DG is the power generated by the diesel generator per hour, C DG_main is the labor maintenance cost of diesel generator, a DG is the diesel generator maintenance cost coefficient, C DG_fu It is the fuel cost per hour for diesel generator.

4. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 2, characterized in that: The economic cost model of wind power generation and photovoltaic power generation is: C WT =c WT ·P WT +λ|P WT -P WTN |·u(t)+a WT ·P WT ; C PV =c PV ·P PV +λ|P PV -P PVN |·u(t)+a PV ·P PV ; Among them, C WT and C PV are the cost models for wind power generation and photovoltaic power generation, c WT and c PV are the electricity price cost per unit power, P WT is the actual output power of the fan, P PV is the actual output power of photovoltaic power, λ is the penalty rate, a WT and a PV are the maintenance cost coefficients of wind power generation and photovoltaic power generation equipment respectively, u(t) is a defined binary variable, u(t) = {0, 1}, when the output power of the wind turbine and photovoltaic array is less than the rated value, u(t) = 0 at this moment, and when it is greater than the rated value, u(t) = 1 at this moment.

5. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 4, characterized in that: The calculation model of the actual output power of the wind turbine and the actual output power of the photovoltaic power is: In the formula, v ci 、v N 、v co are cut-in, rated and cut-out wind speeds respectively, a and b are conversion coefficients, P WTN is the rated output power of the fan; P PVN is the photovoltaic rated power, f PV is the power output efficiency, G PVN is the rated light intensity, ρ is the temperature coefficient, T and T N They are the actual surface temperature and the rated temperature respectively.

6. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 2, characterized in that: The mobile energy storage cost model is: C b =a b ·ζ ij +e b ·|P b |+C tra 4 Among them, C b is the mobile energy storage cost, a b is the fuel consumption per unit time, e b is the unit power aging coefficient, P b is the charging and discharging power of mobile energy storage, C tra For labor costs; ζ ij and l ij are the time and distance taken for the mobile energy storage to be transported from the i-th microgrid to the j-th microgrid, t tra is the traffic jam time per unit distance, v ave is the average speed of the truck, T inst Install time for the device.

7. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 2, characterized in that: In step S2, the economic cost minimization objective function minC is established as: Where i = 1, 2, 3 ... n, represents the number of microgrids, t = 1, 2, 3 ... T represents a certain moment, C DG , C WT , C PV , C b They represent the operating cost of diesel generators, the cost of wind power generation, the cost of photovoltaic power generation and the cost of mobile energy storage respectively.

8. The method for optimizing mobile energy storage and power dispatching in a microgrid according to claim 7, characterized in that: In step S3, the constraints include: P DG_min ≤P DG ≤P DG_max ; P WT_min ≤P WT ≤P WT_max ; P PV_min ≤P PV ≤P PV_max ; P b_min ≤P b ≤P b_max ; SOC min ≤SOC≤SOC max ; Where P DG_min and P DG_max are the minimum and maximum power per hour of the diesel motor, P WT_min and P WT_max are the minimum and maximum output power allowed by the fan, P PV_min and P PV_max are the minimum and maximum output power allowed by the photovoltaic array, P b_min and P b_max They are the minimum or maximum charging and discharging power of mobile energy storage, SOC min and SOC max are the minimum and maximum allowable states of charge for mobile energy storage, SOC is the state of charge for energy storage, P DG , P WT , P PV , P b They are the power generated by the diesel generator per hour, the actual output power of the wind turbine, the actual output power of the photovoltaic power plant, and the charging and discharging power of the mobile energy storage.

Images