Source-load-storage integrated optimal scheduling method and system

Abstract

The invention discloses a source-load-storage integrated optimal scheduling method and system. The method comprises the following steps: S1, constructing a translational load operation constraint condition; s2, constructing a source-load-storage integrated optimal scheduling model objective function; s3, constructing constraint conditions of the source-load-storage integrated optimal scheduling model considering the translational load; and S4, according to the objective function and the constraint condition, solving the source-load-storage integrated optimal scheduling model considering the translational load by adopting a mixed integer linear programming method. By means of the technical scheme, peak load shifting can be effectively achieved, dependence on energy storage equipment is reduced, the utilization rate of distributed energy is increased, the adaptability of the micro-grid to power grid fluctuation can be enhanced, and the economical efficiency and stability of overall operation are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system optimization and dispatching, and in particular relates to a source-load-storage integrated optimization and dispatching method and system. Background Art

[0002] With the continued growth of energy consumption and increasingly severe environmental issues, optimizing the energy structure and improving energy efficiency have become major global issues. As a next-generation energy system, integrated source-load-storage energy systems integrate distributed energy resources, energy storage equipment, and various loads to achieve local energy self-balancing and optimized scheduling. These systems play a significant role in improving renewable energy absorption capacity and reducing carbon emissions.

[0003] In the optimal scheduling of integrated energy systems with sources, loads, and storage, flexible load regulation is an important means to improve system operating efficiency and reduce operating costs. Among them, shiftable loads (i.e., loads that can adjust their operating time within a certain time range) have become an important resource for optimizing the operation of integrated energy systems with sources, loads, and storage due to their strong dispatchability and minimal impact on user comfort. Reasonable scheduling of shiftable loads can not only effectively reduce peak loads and fill valleys, reduce reliance on energy storage equipment, and improve the utilization rate of distributed energy, but also enhance the adaptability of microgrids to grid fluctuations and improve the overall economic and stability of operation. Therefore, studying a method and system for optimizing the scheduling of integrated energy systems with sources, loads, and storage that takes shiftable loads into account has important practical significance for improving the flexibility of integrated energy systems with sources, loads, and storage, promoting efficient energy utilization, and promoting the development of low-carbon smart energy systems. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a source-load-storage integrated optimization scheduling method and system, which can not only effectively reduce peak loads and fill valleys, reduce dependence on energy storage equipment, and improve the utilization rate of distributed energy, but also enhance the adaptability of microgrids to grid fluctuations and improve the economy and stability of overall operation.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A source-load-storage integrated optimization scheduling method includes the following steps:

[0007] Step S1, constructing the operating constraints of the movable load;

[0008] Step S2: constructing the objective function of the source-load-storage integrated optimization scheduling model;

[0009] Step S3: constructing the constraint conditions of the source-load-storage integrated optimization scheduling model taking into account the shiftable load;

[0010] Step S4: Based on the above objective function and constraints, a mixed integer linear programming method is used to solve the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

[0011] Preferably, in step S1, based on the length of the scheduling cycle and the number of translatable loads, the translation state zero-one variable and the load power variable after translation are defined for each translatable load in each time period, and based on the original working period range of the translatable load, the original load power and the acceptable translation period range, the translatable load operation constraint conditions are constructed.

[0012] Preferably, in step S2, an objective function of the source-load-storage integrated optimization scheduling model is constructed based on the compensation cost of shifting shiftable loads, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating cost, the wind and solar power curtailment penalty cost, and the energy storage system operating cost.

[0013] Preferably, in step S3, based on the operating parameters of the gas turbine, wind and photovoltaic power generation systems and the energy storage system, the operating constraints of the gas turbine, the operating constraints of the wind and photovoltaic power generation systems and the energy storage system are constructed, and the upper and lower limit constraints and power balance constraints of the power exchange between the source-load-storage integrated system and the main grid are added to construct the constraints of the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

[0014] The present invention also provides a source-load-storage integrated optimization scheduling system, which is characterized by comprising:

[0015] The first processing module is used to construct the operating constraints of the movable load;

[0016] The second processing module is used to construct the objective function of the source-load-storage integrated optimization scheduling model;

[0017] The third processing module is used to construct the constraint conditions of the source-load-storage integrated optimization scheduling model taking into account the shiftable load;

[0018] The fourth processing module is used to solve the source-load-storage integrated optimization scheduling model taking into account the shiftable load based on the above objective function and constraints using a mixed integer linear programming method.

[0019] Preferably, the first processing module is used to define the translation state zero-one variable and the load power variable after translation for each time period of each translatable load according to the length of the scheduling cycle and the number of translatable loads, and to construct the operating constraints of the translatable load based on the original working time period range, original load power and acceptable translation time period range of the translatable load.

[0020] Preferably, the second processing module is used to construct the objective function of the source-load-storage integrated optimization scheduling model based on the compensation cost of movable load translation, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating cost, the wind and solar power curtailment penalty cost and the energy storage system operating cost.

[0021] Preferably, the third processing module is used to construct the gas turbine operating constraints, wind and photovoltaic power generation system operating constraints, and energy storage system operating constraints based on the operating parameters of the gas turbine, wind and photovoltaic power generation system and the energy storage system, and add the upper and lower limit constraints and power balance constraints of the power exchange between the source-load-storage integrated system and the main grid to construct the constraints of the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

[0022] The present invention improves energy utilization, reduces system operating costs, and enhances system reliability and stability through flexible scheduling of movable loads and other controllable resources in the source-load-storage integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0024] Figure 1 This is a flow chart of the source-load-storage integrated optimization scheduling method according to an embodiment of the present invention;

[0025] Figure 2 The power generation prediction value of the wind power and photovoltaic power generation system and the power curve of the uncontrollable basic load of the system in the source-load-storage integrated energy system of the present invention are as follows;

[0026] Figure 3 is a schematic diagram of load distribution before optimization according to the present invention;

[0027] Figure 4 is a schematic diagram of load distribution after optimization according to the present invention;

[0028] Figure 5 This is a schematic diagram of the unit output considering the translatable load described in the present invention. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] Example 1:

[0032] like Figure 1 As shown, an embodiment of the present invention provides a source-load-storage integrated optimization scheduling method, comprising the following steps:

[0033] Step S1: Define the translation state zero-one variable and the load power variable after translation for each time period of each translatable load according to the scheduling cycle length and the number of translatable loads. Construct the translatable load operation constraint conditions based on the original working time period range, original load power and acceptable translation time period range of the translatable load.

[0034] Step S2: Constructing the objective function of the source-load-storage integrated optimization scheduling model based on the compensation cost for shifting shiftable loads, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating costs, the wind and photovoltaic curtailment penalty costs, and the energy storage system operating cost;

[0035] Step S3: Based on the operating parameters of the gas turbine, wind and photovoltaic power generation systems, and energy storage system, the operating constraints of the gas turbine, wind and photovoltaic power generation systems, and energy storage system are constructed. Furthermore, the upper and lower limits of power exchanged between the integrated source-load-storage system and the main grid, as well as the power balance constraints, are added to construct the constraints of the integrated source-load-storage optimization scheduling model that takes into account the shiftable load.

[0036] Step S4: Based on the above objective function and constraints, a mixed integer linear programming method is used to solve the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

[0037] As an implementation method of the embodiment of the present invention, in step S1, according to the length of the scheduling period and the number of loads that can be translated, the translation state zero-variable u of the load that can be translated in time period t is defined. i,t and translational afterload power variables Based on the original working period range of the translatable load [j i ,n i ]、Original load power and acceptable shift period range The constraints for constructing the translational load operation are as follows:

[0038]

[0039] Because the translatable load can only be translated once at most, the translation starts at a certain moment, that is, there is at most one moment u in the acceptable translation period. i,t =1, so The third equation above indicates that if the load is translated, , then for the non-acceptable translation period (i.e. )of Its value is 0; if the load does not translate, When , then the non-acceptable translation period The value is equal to the original load power The fourth equation in the above formula indicates that if the movable load is translated, then after the translation, the load power at the moment the translation begins is Equal to the power of the load's original starting working period The load power at the next moment after the translation starts is equal to the load power at the next moment after the load originally starts working.

[0040] For example, assuming that the original working period range of the shiftable load i is [j i ,n i ] is [4,6], and the scheduling period is 24 hours, then the original load power vector of each period is for:

[0041]

[0042] Assume that it can accept the translation period range =[10,15]. According to the formula It can be obtained that when t∈[10,15], the load power variable after translation is The values are:

[0043]

[0044] Because there can only be one u i,t is 1, so each of the above equations can only be equal to one of the terms. Assuming that the translation starts at the 10th moment, then u i,10 =1, at other times u i,t is 0, then we can get:

[0045]

[0046] The original load is translated to the 10th, 11th, and 12th moments, which meets the requirements. If, assuming that the translation starts at the 11th moment, then u i,11=1, at other times u i,t is 0, then we can get:

[0047]

[0048] The original load is shifted to the 11th, 12th, and 13th moments, meeting the requirements.

[0049] As an implementation method of the embodiment of the present invention, in step S2, based on the translation compensation cost of the translatable load Main grid electricity purchase cost F net , gas turbine operating cost F gas , wind and photovoltaic power generation system operating costs F wp , wind and photovoltaic power generation system curtailment penalty cost F loss and the battery energy storage system operating cost F bess The objective function of source-load-storage integrated optimization scheduling is constructed as follows:

[0050]

[0051] Among them, NT is the length of the dispatch cycle, NSH is the number of loads that can be shifted, and C sh The unit electricity compensation cost of the shiftable load is Δt, which is the length of the dispatch period, usually 1 hour or 15 minutes. net Time-of-use electricity price, is the exchange power between the source-load-storage integrated system and the main grid in time period t, C gas is the unit natural gas cost, The natural gas consumption of the i-th gas turbine unit in period t, NGT is the number of gas turbines, NW is the number of wind turbines, NPV is the number of photovoltaic units, C w is the wind power operation cost coefficient, is the power generation of the i-th wind power generation system in time period t, C pv is the operating cost coefficient of the photovoltaic power generation system, is the power of the ith photovoltaic power generation system in time period t, C wl is the penalty cost coefficient for curtailment of wind power generation system, is the abandoned power of the i-th wind power generation system in time period t, C pvl is the penalty cost coefficient for power abandonment of photovoltaic power generation system, is the abandoned power of the ith photovoltaic power generation system in time period t, NBES is the total number of battery energy storage systems, C bess is the operating cost coefficient of the battery energy storage system, are the charging and discharging power of the i-th battery energy storage system in time period t.

[0052] As an implementation method of an embodiment of the present invention, in step S3, based on the operating parameters of the gas turbine, wind power generation system, photovoltaic power generation system, and energy storage system, their respective operating constraints are constructed, and combined with the operating constraints of the shiftable load, a source-load-storage integrated optimization scheduling model constraint taking into account the shiftable load is established.

[0053] The gas turbine operating constraints are:

[0054]

[0055] in, is the power generation efficiency of the gas turbine, L NG is the calorific value of natural gas, is the output of the i-th gas turbine in time period t, are the upper and lower limits of gas turbine output, are the maximum power of the gas turbine under up-climbing and down-climbing constraints, respectively.

[0056] The operating constraints of the wind power generation and photovoltaic power generation systems are:

[0057]

[0058] in, is the predicted power generation value of the i-th wind power generation system in time period t, is the predicted power generation value of the i-th photovoltaic power generation system in time period t.

[0059] The operating constraints of the battery energy storage system are:

[0060]

[0061] in, are the 0-1 variables of charging and discharging of the i-th battery energy storage system in time period t, are the charging and discharging power of the i-th battery energy storage system in time period t, are the upper and lower limits of the charging power of the i-th battery energy storage system, are the upper and lower limits of the discharge power of the i-th battery energy storage system, is the capacity of the battery during period t, are the charging efficiency and discharging efficiency of the i-th battery energy storage system, are the upper and lower limits of the capacity of the i-th battery energy storage system, is the capacity of the i-th battery energy storage system at the end of the scheduling period, is the initial state capacity of the i-th battery energy storage system.

[0062] The upper and lower limit constraints of the power exchange between the source-load-storage integrated system and the main power grid are:

[0063]

[0064] in, It is the upper limit of the power exchanged between the integrated source-load-storage system and the main power grid.

[0065] The power balance constraint condition is:

[0066]

[0067] in, is the power of the uncontrollable basic load of the integrated source-load-storage system in time period t.

[0068] As one embodiment of the present invention, in step S4, based on the above objective function and constraints, a GUROBI optimization solver of a mixed integer linear programming model is used to obtain a source-load-storage integrated optimization scheduling result taking into account the shiftable load.

[0069] The embodiment of the present invention will study several cases to demonstrate the effectiveness and advantages of the proposed model for optimizing the scheduling of source-load-storage integration with shiftable loads. The example selects the source-load-storage integration system in a certain area as the research object, which includes wind power generation system, photovoltaic power generation system, gas turbine and battery energy storage system. 24h is a scheduling cycle and 1h is a scheduling period. The operating parameters of the source-load-storage integration system are shown in Table 1, the time-of-use electricity price is shown in Table 2, and the shiftable load parameters are shown in Table 3. The predicted power generation value of the wind and photovoltaic power generation system and the predicted power curve of the system's uncontrollable load are shown in Table 3. Figure 2 .

[0070] Table 1

[0071] type Power lower limit / kW Power upper limit / kW <![CDATA[Operating cost / yuan·(kWh) -1 > Main power grid -180 180 Time-of-use electricity price wind power 0 Predicted value 0.5 Photovoltaics 0 Predicted value 0.6 gas turbine 0 80 Natural gas prices

[0072] Table 2

[0073] Electricity price period Time period (h) Electricity price (yuan / kWh) Flat section 7:00-10:00、15:00-18:00、21:00-24:00 0.53 Valley Section 1:00-6:00 0.25 Peak section 11:00-14:00、19:00-20:00 0.82

[0074] Table 3

[0075]

[0076] Two case studies were conducted in the simulation:

[0077] Case 1: Integrated source-load-storage system without considering shiftable load regulation

[0078] Case 2: Integrated source-load-storage system with shiftable load regulation

[0079] All case studies were programmed using MATLAB 2019b with the YALMIP toolbox and solved using the Gurobi 10.0.2 optimization solver. Simulation experiments for Cases 1 and 2 demonstrated that the integrated power-load-storage system significantly reduces operating costs and improves overall energy efficiency when operating in a mode that incorporates shiftable loads. This demonstrates the crucial role shiftable loads play in optimizing power dispatch in integrated power-load-storage systems.

[0080] The operational planning results shown in Table 4 demonstrate that, after optimized scheduling, the integrated source-load-storage system including a shiftable load can achieve the lowest operating cost, demonstrating the effectiveness of the proposed method in optimizing economic efficiency. Table 5 further shows that, after implementing the proposed method, the integrated source-load-storage system's renewable energy output has been increased, promoting the effective absorption of renewable energy and enhancing the system's energy efficiency and scheduling flexibility.

[0081] Table 4

[0082] Operation Mode Case 1 Case 2 Cost (yuan) 3415.8 3392.9

[0083] Table 5

[0084] Operation Mode Case 1 Case 2 New energy output (kW) 3360 3400

[0085] Figure 3 and Figure 4 As shown, it can be seen that the movable load 1 is shifted from the original 12:00-13:00 period to the 5:00-6:00 period, and the movable load 2 is shifted from the original 18:00-20:00 period to the 7:00-9:00 period.

[0086] Figure 5 The comparison of the electric load curve before optimization and the electric load curve after optimization shows that when the shiftable load is taken into account, the load is more balanced and the peak-shaving and valley-filling effect is significant.

[0087] Example 2:

[0088] An embodiment of the present invention further provides a source-load-storage integrated optimization scheduling system, which is characterized by comprising:

[0089] The first processing module is used to construct the operating constraints of the movable load;

[0090] The second processing module is used to construct the objective function of the source-load-storage integrated optimization scheduling model;

[0091] The third processing module is used to construct the constraint conditions of the source-load-storage integrated optimization scheduling model taking into account the shiftable load;

[0092] The fourth processing module is used to solve the source-load-storage integrated optimization scheduling model taking into account the shiftable load based on the above objective function and constraints using a mixed integer linear programming method.

[0093] As an implementation method of an embodiment of the present invention, the first processing module is used to define the translation state zero-one variable and the load power variable after translation of each translatable load in each time period according to the length of the scheduling cycle and the number of translatable loads, and construct the translatable load operation constraint conditions based on the original working time period range, original load power and acceptable translation time period range of the translatable load.

[0094] As an implementation method of an embodiment of the present invention, the second processing module is used to construct an objective function of the source-load-storage integrated optimization scheduling model based on the compensation cost of shifting movable loads, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating cost, the wind and solar power curtailment penalty cost and the energy storage system operating cost.

[0095] As an implementation method of an embodiment of the present invention, the third processing module is used to construct the gas turbine operation constraints, wind and photovoltaic power generation system operation constraints, and energy storage system operation constraints based on the operating parameters of the gas turbine, wind and photovoltaic power generation system and the energy storage system, and add the upper and lower limit constraints and power balance constraints of the power exchange between the source-load-storage integrated system and the main grid to construct the constraint conditions of the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

[0096] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A source-load-storage integrated optimization scheduling method, characterized in that: The following steps are involved: Step S1, constructing the operating constraints of the movable load; Step S2: constructing the objective function of the source-load-storage integrated optimization scheduling model; Step S3: constructing the constraint conditions of the source-load-storage integrated optimization scheduling model taking into account the shiftable load; Step S4: Based on the above objective function and constraints, a mixed integer linear programming method is used to solve the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

2. The source-load-storage integrated optimization scheduling method according to claim 1, characterized in that: In step S1, based on the length of the scheduling cycle and the number of translatable loads, the translation state zero-one variable and the load power variable after translation are defined for each translatable load in each time period. Based on the original working period range of the translatable load, the original load power and the acceptable translation period range, the translatable load operation constraint conditions are constructed.

3. The source-load-storage integrated optimization scheduling method according to claim 2, characterized in that: In step S2, the objective function of the source-load-storage integrated optimization scheduling model is constructed based on the compensation cost of shiftable loads, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating cost, the wind and solar power curtailment penalty cost, and the energy storage system operating cost.

4. The source-load-storage integrated optimization scheduling method according to claim 3, characterized in that: In step S3, based on the operating parameters of the gas turbine, wind and photovoltaic power generation systems, and energy storage systems, the operating constraints of the gas turbine, wind and photovoltaic power generation systems, and energy storage systems are constructed. In addition, the upper and lower limit constraints on the power exchange between the source-load-storage integrated system and the main grid and the power balance constraints are added to construct the constraints of the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

5. A source-load-storage integrated optimization scheduling system, characterized in that: include: The first processing module is used to construct the translation load operation constraint conditions; The second processing module is used to construct the objective function of the source-load-storage integrated optimization scheduling model; The third processing module is used to construct the constraint conditions of the source-load-storage integrated optimization scheduling model taking into account the shiftable load; The fourth processing module is used to solve the source-load-storage integrated optimization scheduling model taking into account the shiftable load based on the above objective function and constraints using a mixed integer linear programming method.

6. The source-load-storage integrated optimization scheduling system according to claim 5, characterized in that: The first processing module is used to define the translation state zero-one variable and the load power variable after translation for each time period of each translatable load according to the length of the scheduling cycle and the number of translatable loads, and to construct the translatable load operation constraint conditions based on the original working time period range, original load power and acceptable translation time period range of the translatable load.

7. The source-load-storage integrated optimization scheduling system according to claim 6, characterized in that: The second processing module is used to construct the objective function of the source-load-storage integrated optimization scheduling model based on the compensation cost of movable load translation, the main grid electricity purchase cost, the gas turbine operating cost, the wind and photovoltaic power generation system operating cost, the wind and solar power curtailment penalty cost and the energy storage system operating cost.

8. The source-load-storage integrated optimization scheduling system according to claim 7, characterized in that: The third processing module is used to construct the gas turbine operating constraints, wind and photovoltaic power generation system operating constraints, and energy storage system operating constraints based on the operating parameters of the gas turbine, wind and photovoltaic power generation system, and energy storage system. In addition, the upper and lower limit constraints and power balance constraints of the power exchange between the source-load-storage integrated system and the main grid are added to construct the constraints of the source-load-storage integrated optimization scheduling model that takes into account the shiftable load.

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