Peak clipping and valley filling method and device for photovoltaic microgrid

Abstract

The invention provides a peak clipping and valley filling method and device for a photovoltaic micro-grid, and the method comprises the following steps: creating a peak clipping and valley filling model corresponding to the photovoltaic micro-grid, setting the energy state of an energy storage battery at a moment t + 1, and the target function and constraint conditions of the peak clipping and valley filling model, and then, carrying out the peak clipping and valley filling of the photovoltaic micro-grid. And carrying out optimization processing on the peak clipping and valley filling model. The peak clipping and valley filling method can greatly improve the stability and reliability of the DC microgrid.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic technology, and in particular to a peak shaving and valley filling method and a device thereof for a photovoltaic microgrid. Background Art

[0002] With the development of renewable energy technology and the modernization of power systems, DC microgrids are gaining more and more attention due to their high efficiency and simplified power conversion process. Due to the instability of photovoltaic power generation, if photovoltaic power generation equipment is connected to the grid at the same time, it will cause a high load on the transmission network. The relevant method is to equip photovoltaic power generation equipment with energy storage equipment, store energy during peak power consumption periods, and connect to the grid during off-peak periods. However, this management method is relatively extensive, and the predicted peak and off-peak periods are not quite consistent with the actual situation of the transmission network.

[0003] Therefore, if the DC microgrid is to be peak-shaving and valley-filling, it becomes an urgent problem to be solved. Summary of the invention

[0004] The object of the present invention is to provide a peak shaving and valley filling method and device for a photovoltaic microgrid.

[0005] In order to achieve one of the above-mentioned invention purposes, an embodiment of the present invention provides a peak shaving and valley filling method for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with a photovoltaic power generation device, an energy storage battery and a load; the method comprises the following steps: creating a peak shaving and valley filling model corresponding to the photovoltaic microgrid, the energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P charge (t),P discharge (t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P load (t); where C and Pmax are constants, P PV(t) is the power generation of the photovoltaic power generation equipment at time t, P load (t) the power consumption of the load at time t; optimizing the peak shaving and valley filling model to obtain the optimized P charge (1) P charge (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

[0006] As a further improvement of an implementation manner of the present invention, the “optimizing the peak shaving and valley filling model” specifically includes: optimizing the peak shaving and valley filling model based on a linear programming algorithm.

[0007] As a further improvement of an implementation manner of the present invention, the “optimizing the peak shaving and valley filling model” specifically includes: optimizing the peak shaving and valley filling model based on a nonlinear programming algorithm.

[0008] As a further improvement of an implementation manner of the present invention, the “optimizing the peak shaving and valley filling model” specifically includes: optimizing the peak shaving and valley filling model based on a dynamic programming algorithm.

[0009] As a further improvement of one embodiment of the present invention, Δt is 1 hour.

[0010] The embodiment of the present invention also provides a peak shaving and valley filling device for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with photovoltaic power generation equipment, energy storage batteries and loads; and comprises the following modules: a model creation module, which is used to create a peak shaving and valley filling model corresponding to the photovoltaic microgrid, and the energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P charge (t),P discharge(t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P load (t); where C and Pmax are constants, P PV (t) is the power generation of the photovoltaic power generation equipment at time t, P load (t) the power consumption of the load at time t; an optimization module, used to optimize the peak shaving and valley filling model to obtain the optimized P charge (1) P charge (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

[0011] As a further improvement of an embodiment of the present invention, the optimization module is further used to: optimize the peak shaving and valley filling model based on a linear programming algorithm.

[0012] As a further improvement of an implementation mode of the present invention, the optimization module is further used to: optimize the peak shaving and valley filling model based on a nonlinear programming algorithm.

[0013] As a further improvement of an embodiment of the present invention, the optimization module is further used to: optimize the peak shaving and valley filling model based on a dynamic programming algorithm.

[0014] As a further improvement of one embodiment of the present invention, Δt is 1 hour.

[0015] Compared with the prior art, the technical effect of the present invention is that: the embodiment of the present invention provides a peak-shaving and valley-filling method and device for a photovoltaic microgrid, and the peak-shaving and valley-filling method comprises the following steps: creating a peak-shaving and valley-filling model corresponding to the photovoltaic microgrid, and setting the energy state of the energy storage battery at time t+1, the objective function and constraint conditions of the peak-shaving and valley-filling model, and then optimizing the peak-shaving and valley-filling model. The peak-shaving and valley-filling method can greatly improve the stability and reliability of the DC microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a peak shaving and valley filling method for a photovoltaic microgrid in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be described in detail below in conjunction with the various embodiments shown in the accompanying drawings. However, these embodiments do not limit the present invention, and any structural, methodological, or functional changes made by a person skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0018] As used herein, terms indicating spatial relative positions such as "upper," "above," "lower," and "below" are used for the purpose of convenience to describe the relationship of one unit or feature relative to another unit or feature as shown in the accompanying drawings. Terms of spatial relative position may be intended to include different orientations of the device in use or operation in addition to the orientation shown in the drawings. For example, if the device in the figure is turned over, units described as being "below" or "beneath" other units or features will be located "above" the other units or features. Thus, the exemplary term "below" can encompass both above and below orientations. The device may be oriented in other ways (rotated 90 degrees or in other orientations), and the spatially relative descriptors used herein interpreted accordingly.

[0019] Embodiment 1 of the present invention provides a peak shaving and valley filling method for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with a photovoltaic power generation device, an energy storage battery and a load; Figure 1 As shown, the following steps are included:

[0020] Step 101: Create a peak-shaving and valley-filling model corresponding to the photovoltaic microgrid. The energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P chargc (t),P discharge (t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P load (t); where C and Pmax are constants, P PV (t) is the power generation of the photovoltaic power generation equipment at time t, P load(t) The power consumption of the load at time t; Peak shaving and valley filling is a strategy for peak load regulation in photovoltaic power generation, which aims to balance the difference between power supply and demand. In the power system, the load fluctuates greatly, especially the load difference between peak and valley periods is large. In order to meet the demand during peak periods, additional power generation capacity is usually required, while there may be excess power generation capacity during valley periods.

[0021] The peak shaving and valley filling strategy in the energy storage industry refers to the use of energy storage technology to adjust the grid load through the storage and release of energy storage equipment when the power system load fluctuates greatly, so as to balance the supply and demand differences and improve the stability and reliability of the grid.

[0022] The peak shaving and valley filling strategy mainly includes two aspects of application: peak shaving and valley filling.

[0023] Peak shaving: During the peak load period of the power system, the energy storage function of the energy storage equipment is used to store excess electric energy to avoid overload of the power grid. When the load demand decreases, the stored electric energy is released to meet the needs of the power grid. This can reduce the use of traditional power generation methods such as thermal power plants, reduce carbon emissions and energy consumption.

[0024] Valley filling: During the low load period of the power system, the stored electric energy is released through the release function of the energy storage equipment to meet the needs of the power grid. This can make up for the power supply shortage of the power system during the low load period and improve the power supply capacity of the power grid.

[0025] The country promotes time-of-use electricity prices. The electricity prices in different periods are generally peak > peak > normal > valley. The theoretical electricity consumption in different periods is generally peak > peak > normal > valley. Therefore, peak shaving and valley filling can achieve peak-valley arbitrage (for details, please refer to the peak-valley arbitrage concept below).

[0026] Here, through the peak shaving and valley filling model, electric energy can be stored during peak electricity consumption periods and released during low electricity consumption periods. According to the electricity spot trading rules, the special characteristics of the "peak-flat-valley" curve are seized to adjust the power generation by "peak shaving and valley filling", which helps to reduce the electricity costs of enterprises during peak electricity consumption periods and maintain stable power supply during low electricity consumption periods.

[0027] Step 102: Optimize the peak shaving and valley filling model to obtain the optimized P charge (1) P charge (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

[0028] Here, C elec(t) is the electricity price at time t. When t=0, it can be considered as the initial state of the peak shaving and valley filling model. At this time, the initial value of E(t) needs to be set. It is necessary to obtain the energy states E(1), E(2), ..., E(t) of the peak shaving and valley filling model, and the charging power P charhe (1) P charge (2), ..., P charge (t), discharge power P discharge (1) P discharge (2), ..., P discharge (t),In practice, the acquired data is usually uneven, so it is necessary to clean the acquired data, process outliers and missing values, and ensure data quality. The goal of this peak shaving and valley filling model is to ensure that the charging and discharging operations of the energy storage system operate within a reasonable range and minimize the sum of electricity costs and operating costs.

[0029] In this embodiment, the "optimizing the peak shaving and valley filling model" specifically includes: optimizing the peak shaving and valley filling model based on a linear programming algorithm. Here, the linear programming algorithm includes three elements: (1) decision variables, which are unknown quantities to be determined in the problem, used to indicate the schemes and measures expressed in quantities in the planning problem, which can be determined and controlled by the decision maker; (2) objective function, which is a function of the decision variables, and the optimization goal is usually to find the maximum or minimum value of the function; (3) constraints, which are the constraints and restrictions on the values ​​of the decision variables, usually expressed by equations or inequalities containing the decision variables.

[0030] In this embodiment, the "optimization of the peak shaving and valley filling model" specifically includes: optimizing the peak shaving and valley filling model based on a nonlinear programming algorithm. Here, nonlinear programming generally includes the following steps: (1) First, information and data related to the problem should be collected, and on the basis of a comprehensive understanding of the problem, what are the available solutions to the problem, and use a set of variables to represent them; (2) After analyzing the information, according to actual needs and possibilities, propose the goal of minimization or maximization to be pursued, and use various scientific and technological principles to express it as a mathematical relationship; (3) After proposing the goal to be pursued, it is necessary to establish the value standard of "good" or "bad" of the considered goal and describe it in a certain quantitative form; (4) Since the goal to be pursued generally requires minimization or maximization under certain conditions, it is also necessary to find all the constraints of the problem, and these conditions are usually represented by some inequalities or equations between variables.

[0031] In this embodiment, the "optimizing the peak shaving and valley filling model" specifically includes: optimizing the peak shaving and valley filling model based on the dynamic programming algorithm. Here, the dynamic programming algorithm is usually used to solve problems with certain optimal properties. In this type of problem, there may be many feasible solutions. Each solution corresponds to a value, and we hope to find the solution with the optimal value. The dynamic programming algorithm is similar to the divide-and-conquer method, and its basic idea is to decompose the problem to be solved into several sub-problems, solve the sub-problems first, and then obtain the solution to the original problem from the solutions of these sub-problems. Unlike the divide-and-conquer method, the sub-problems that are suitable for solving by dynamic programming are often not independent of each other after decomposition. If the divide-and-conquer method is used to solve this type of problem, the number of sub-problems obtained by decomposition is too large, and some sub-problems are repeatedly calculated many times. If the answers to the solved sub-problems can be saved, and the answers obtained can be found when needed, a large amount of repeated calculations can be avoided, saving time.

[0032] In this embodiment, Δt is 1 hour.

[0033] In the inventor's practice, the following experiments were conducted:

[0034] A small photovoltaic microgrid includes: (1) photovoltaic production capacity, with a maximum output of 50kW; (2) load demand, with daily average demand varying between 30kW and 60kW; (3) energy storage system, with a maximum capacity of 100kWh, a maximum charge / discharge rate of 10kW, and a charge / discharge efficiency of 90%.

[0035] Implementation steps

[0036] Step 1: Initial setting: At the beginning of a certain day, it is assumed that the energy storage system is fully charged.

[0037] Step 1: Rolling optimization execution: Run the optimization model every hour based on the PV output forecast and load demand; use the predicted PV output and real-time load data to calculate the optimal charging and discharging strategy every hour.

[0038] Specific hours of operation

[0039] At 9:00AM, the PV output forecast is 40kW, the actual load demand is 45kW, and the decision is to discharge 5kW to meet the load gap.

[0040] At 12:00PM, the PV output forecast is 50kW, the actual load demand is 30kW, and the decision is to charge 20kW (using excess PV output).

[0041] Model solving and updating: In each rolling time domain, the optimization model is updated based on the latest photovoltaic and load data to adjust the charging and discharging plan for the next few hours. This process involves real-time data acquisition, model updating and solving, which requires ensuring fast and accurate data processing and optimization solving capabilities. In this way, photovoltaic microgrids can effectively use energy storage systems to shave peaks and fill valleys, enhance the system's energy self-sufficiency, reduce energy costs, and improve the system's utilization of renewable energy.

[0042] Embodiment 2 of the present invention provides a peak shaving and valley filling device for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with photovoltaic power generation equipment, energy storage batteries and loads; and comprises the following modules:

[0043] Model creation module, used to create the peak shaving and valley filling model corresponding to the photovoltaic microgrid, the energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P charge (t),P discharge (t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P load (t); where C and Pmax are constants, P PV (t) is the power generation of the photovoltaic power generation equipment at time t, P load (t) the power consumption of the load at time t;

[0044] The optimization module is used to optimize the peak shaving and valley filling model to obtain the optimized P charge (1) P chargc (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

[0045] In this embodiment, the optimization module is further used to optimize the peak shaving and valley filling model based on a linear programming algorithm.

[0046] In this embodiment, the optimization module is further used to optimize the peak shaving and valley filling model based on a nonlinear programming algorithm.

[0047] In this embodiment, the optimization module is further used to optimize the peak shaving and valley filling model based on a dynamic programming algorithm.

[0048] In this embodiment, Δt is 1 hour.

[0049] It should be understood that although this specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each implementation mode may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0050] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A peak shaving and valley filling method for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with photovoltaic power generation equipment, energy storage batteries and loads; characterized in that: The following steps are involved: Create a peak shaving and valley filling model corresponding to the photovoltaic microgrid, and the energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P charge (t),P discharge (t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P ioad (t); where C and Pmax are constants, P PV (t) is the power generation of the photovoltaic power generation equipment at time t, P load (t) the power consumption of the load at time t; The peak shaving and valley filling model is optimized to obtain the optimized P charge (1) P charge (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

2. The peak shaving and valley filling method according to claim 1, characterized in that: The “optimizing the peak shaving and valley filling model” specifically includes: Based on a linear programming algorithm, the peak shaving and valley filling model is optimized.

3. The peak shaving and valley filling method according to claim 1, characterized in that: The “optimizing the peak shaving and valley filling model” specifically includes: Based on a nonlinear programming algorithm, the peak shaving and valley filling model is optimized.

4. The peak shaving and valley filling method according to claim 1, characterized in that: The “optimizing the peak shaving and valley filling model” specifically includes: Based on a dynamic programming algorithm, the peak shaving and valley filling model is optimized.

5. The peak shaving and valley filling method according to claim 1, characterized in that: Δt is 1 hour.

6. A peak-shaving and valley-filling device for a photovoltaic microgrid, wherein the photovoltaic microgrid is provided with photovoltaic power generation equipment, energy storage batteries and loads; characterized in that: Includes the following modules: Model creation module, used to create the peak shaving and valley filling model corresponding to the photovoltaic microgrid, the energy state of the energy storage battery at time t+1 E(t) is the energy state of the energy storage battery at time t, P charge (t) is the charging power of the energy storage battery at time t, P discharge (t) is the discharge power of the energy storage battery at time t, Δt is the time interval between time t+1 and time t, η charge is the charging efficiency of the energy storage battery, η discharge is the discharge efficiency of the energy storage battery, where t and T are natural numbers, 1≤t≤T; the objective function of the peak shaving and valley filling model is Among them, C elec (t) is the unit cost of electricity at time t, C op () is the cost function of the charge and discharge operation, T is a natural number, T ≥ 2; the constraints are: 0 ≤ E (t) ≤ C, 0 ≤ P charge (t),P discharge (t)≤Pmax,P PV (t)+P discharge (t)-P charge (t) = P load (t); where C and Pmax are constants, P PV (t) is the power generation of the photovoltaic power generation equipment at time t, P load (t) the power consumption of the load at time t; The optimization module is used to optimize the peak shaving and valley filling model to obtain the optimized P charge (1) P charge (2), ..., P charge (T) and P discharge (1) P discharge (2), ..., P discharge (T).

7. The peak shaving and valley filling device according to claim 6, characterized in that: The optimization module is also used to: Based on a linear programming algorithm, the peak shaving and valley filling model is optimized.

8. The peak shaving and valley filling device according to claim 6, characterized in that: The optimization module is also used to: Based on a nonlinear programming algorithm, the peak shaving and valley filling model is optimized.

9. The peak shaving and valley filling device according to claim 6, characterized in that: The optimization module is also used to: Based on a dynamic programming algorithm, the peak shaving and valley filling model is optimized.

10. The peak shaving and valley filling device according to claim 6, characterized in that: Δt is 1 hour.

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