A microgrid economic dispatch method considering energy storage cycle life

Abstract

The application discloses a micro-grid economic dispatching method considering energy storage cycle life. The method comprises the following steps: reading local electrical data; calculating energy storage discharge depth and linearizing a function to obtain energy storage life loss cost of different energy storage discharge depths; establishing a micro-grid economic dispatching model with the minimum micro-grid daily operation cost as an objective, wherein the micro-grid daily operation cost comprises energy storage life loss cost, power purchase and sale cost, operation and maintenance cost of each unit and fuel cost; and solving the micro-grid economic dispatching model, and formulating energy storage charging and discharging strategy and power purchase strategy for the micro-grid according to obtained model decision variables. The micro-grid operation dispatching model established by the application considers new energy units, steam turbine units and energy storage, can improve micro-grid economic dispatching benefit through good multi-energy complementation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of micro-grid economic dispatch, and particularly relates to a micro-grid economic dispatch method considering the cycle life of energy storage. BACKGROUND

[0002] Micro-grid has been widely used in power system because it can effectively consume clean energy. Energy storage technology, as a core element of energy internet development, plays an important role in power balance and can effectively cope with the randomness and volatility of new energy. However, the high investment cost and limited cycle life of energy storage system have become key factors restricting the realization of good economic effect in the process of energy storage planning.

[0003] Under this background, the collaborative optimization and dispatch of micro-grid energy storage and source-load, and the comprehensive consideration of factors such as energy storage cycle life, can not only promote the efficient use of clean and renewable power, but also effectively reduce peak load, which has far-reaching significance for ensuring the stable and safe operation of micro-grid and improving the investment economy of energy storage.

[0004] In existing research, the micro-grid economic dispatch research lacks consideration from the source-load-storage perspective and the influence of energy storage charge-discharge times on energy storage life. However, with the continuous access of new energy and the increasing demand for load, higher requirements are put forward for the function of energy storage, but frequent charge-discharge will cause the decline of energy storage cycle life. The existing energy storage planning model only considers the influence of energy storage charge-discharge times on energy storage life, cannot well quantify and calculate the life conversion cost of energy storage, leads to the calculation result of economic benefit of actual configured micro-grid being prone to be large, does not conform to the actual situation, and cannot obtain a micro-grid economic dispatch method for reducing the cycle life loss value of energy storage (Chen Mingyang, Liu Min, Yu Dengwu. Micro-grid economic dispatch considering energy storage life. Intelligent Computer and Applications, 2021, 11(10): 101-106.). SUMMARY

[0005] The present application aims to solve the problem that the existing micro-grid economic dispatch model lacks consideration of the influence of energy storage charge-discharge times on energy storage life, and proposes a micro-grid economic dispatch method considering the cycle life of energy storage, that is, the influence of energy storage charge-discharge times on energy storage life, combined with new energy output data and load data, to establish a micro-grid economic dispatch model and obtain a micro-grid economic dispatch scheme.

[0006] The purpose of the present application is achieved at least by one of the following technical solutions.

[0007] A micro-grid economic dispatch method considering the cycle life of energy storage, comprising the following steps:

[0008] S1, read the local electrical data;

[0009] S2, calculate the energy storage discharge depth and linearize the function to obtain the energy storage life loss cost at different energy storage discharge depths;

[0010] S3, establish a micro-grid economic dispatching model with the minimum micro-grid daily operation cost as the target, the micro-grid daily operation cost including energy storage life loss cost, electricity purchase and sale cost, operation and maintenance cost of each unit, and fuel cost;

[0011] S4, solve the micro-grid economic dispatching model, and formulate the energy storage charging and discharging strategy and the electricity purchase strategy for the micro-grid according to the obtained model decision variables.

[0012] Further, in step S1, the electrical data includes: peak-valley electricity price, wind turbine and photovoltaic output data, load data, upper limit P G.min of gas turbine output, lower limit P G.max of gas turbine output, operation and maintenance cost c om.W of wind turbine, operation and maintenance cost c om.PV of photovoltaic, operation and maintenance cost c om.G of gas turbine, unit cost c fuel of fuel, operation and maintenance cost c om.bat of energy storage, charging and discharging efficiency η of energy storage, upper limit SOC max of energy storage power, lower limit SOC min of energy storage power, and upper limit P grid.max of tie line.

[0013] Further, in step S2, the following steps are included:

[0014] S2.1, divide 100% discharge depth into 5 segments, calculate the discharge depth of energy storage at time t, and determine the charging and discharging state coefficient, specifically as follows:

[0015]

[0016] Wherein, g d (t) is the charging and discharging state coefficient of energy storage at the dth segment of discharge depth, if the discharge depth of energy storage at time t is located in the dth segment, then the charging and discharging state coefficient g d (t) of energy storage at the dth segment of discharge depth is 1, otherwise g d (t) is 0, 1≤d≤5; SOC(t) represents the state of charge of energy storage at time t; d d (t) represents the dth segment of discharge depth of energy storage at time t; dod d are the upper and lower limits of the dth segment of discharge depth respectively; g d (t) is the charging and discharging state coefficient of energy storage at the dth segment of discharge depth;

[0017] S2.2, according to the charge-discharge state coefficient, the minimum value of the exponential function formula is linearized for different discharge depth intervals, and the linearization coefficient K of the energy storage at the dth discharge depth is determined d , B d , as follows:

[0018] kpand kdare determined by the type of energy storage;

[0019] S2.3, linearizing the energy storage cycle count variable S bat (t) at time t, as follows:

[0020]

[0021] wherein U bat (t) is 0 indicates that the energy storage is discharged, and U bat (t) is 1 indicates that the energy storage is charged;

[0022] S2.4, according to the linearization coefficient K of the energy storage at the dth discharge depth d , B d and the cycle count variable S bat (t) at time t, the energy storage life loss cost C bat is calculated, as follows:

[0023]

[0024] wherein M represents a very large number.

[0025] Further, in step S3, the objective function of the microgrid economic dispatching model is represented as follows:

[0026] min C = min {C ope} (1)

[0027] C ope = C grid + C om + C fuel + C bat (2)

[0028]

[0029] wherein C is the comprehensive operation cost of the microgrid; C ope is the daily operation cost of the microgrid; p is the discount rate, r is the discount years, C grid , C om and C fuel are the purchase and sale electricity cost, the operation and maintenance cost of each unit and the fuel cost, respectively, c grid (t) is the electricity price of the grid at time t, c fuelThe fuel unit cost; c om.W 、c om.PV 、c om.G 、c om，bat The operation and maintenance cost coefficients of the fan, photovoltaic, gas turbine, and energy storage, respectively; P buy (t) and P sell (t) are the purchased and sold power of the microgrid at time t, respectively; P G (t), P W (t), and P PV (t) are the output powers of the gas turbine, fan, and photovoltaic at time t, respectively; P ch (t), P dis (t) are the charging and discharging powers of the energy storage at time t; and Δt is the time step.

[0030] Further, in step S3, the constraint conditions of the microgrid economic dispatching model include gas turbine constraints, power grid power purchase constraints, energy storage power and energy constraints, and power balance constraints.

[0031] Further, the gas turbine constraints are as follows:

[0032] P G.min ≤P G (t)≤P G.max (4)

[0033] wherein P G.min and P G.max are the upper and lower limits of the micro gas turbine output, respectively, which are limited by the minimum load rate and the rated power;

[0034] The microgrid energy constraints are as follows:

[0035]

[0036] wherein P buy (t) and P sell (t) are the purchased and sold power of the microgrid at time t, respectively; P grid.max is the upper limit of the interactive power of the tie line between the microgrid and the power grid; U grid (t) is the state variable of the microgrid power purchase and sale at time t, 1 representing power purchase and 0 representing power sale.

[0037] Further, the energy storage power and energy constraints include energy storage charging and discharging power constraints and energy storage state of charge (SOC) constraints;

[0038] The energy storage charging and discharging power constraints are as follows:

[0039]

[0040] Pbat.max = μE bat.max (7)

[0041] wherein, P dis (t), P ch (t) are the discharging and charging power of the energy storage at time t respectively; P bat.max is the upper limit of the energy storage charging and discharging power, and μ is a fixed proportional coefficient of the upper limit of the energy storage power and the rated capacity E bat.max ;

[0042] Energy storage state of charge (SOC) constraint:

[0043]

[0044] wherein, Δt is a time step, taking 1h; E(0) is the initial electric quantity of the energy storage, SOC max , SOC min are the upper and lower limits of the state of charge of the energy storage respectively, and η is the charging and discharging efficiency of the energy storage.

[0045] Further, the power balance constraint is as follows:

[0046] P dis (t) - P ch (t) + P buy (t) - P sell (t) + P G (t) = 0 (10).

[0047] Further, in step S4, the model decision variables are solved by a commercial solver clpex, including: the discharging and charging power P dis (t) and P ch (t) of the energy storage system at time t, and the purchasing and selling power P buy (t) and P sell (t) of the microgrid at time t.

[0048] Compared with the prior art, the advantages of the present application are:

[0049] 1. The microgrid operation scheduling model established in the present application considers new energy units, steam turbine units and energy storage, and can improve the economic scheduling benefit of the microgrid through good multi-energy complementation;

[0050] 2. The energy storage life loss cost and the cycle count variable are linearized in the present application, the cycle life loss cost of the energy storage is calculated when calculating the energy storage discharge depth, so that the microgrid scheduling is beneficial to improve the life of the energy storage, and the result is more realistic. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1A flow chart of steps of a micro-grid economic dispatch method considering energy storage cycle life in an embodiment of the present application;

[0052] Figure 2 A photovoltaic and wind turbine output and load parameter schematic diagram in an embodiment of the present application;

[0053] Figure 3 A micro-grid optimization operation result schematic diagram not considering energy storage cycle life in an embodiment of the present application;

[0054] Figure 4 A micro-grid optimization operation result schematic diagram considering energy storage cycle life in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the present application more clear, specific embodiments of the present application are described in detail below with reference to the accompanying drawings and embodiments.

[0056] Embodiment:

[0057] A micro-grid economic dispatch method considering energy storage cycle life, as shown in Figure 1 , includes the following steps:

[0058] S1, read local electrical data;

[0059] The electrical data includes: peak-valley electricity price, wind turbine and photovoltaic output data, load data, gas turbine output upper limit P G.min , gas turbine output lower limit P G.max , wind turbine operation and maintenance cost c om.W , photovoltaic operation and maintenance cost c om.PV , gas turbine operation and maintenance cost c om.G , fuel unit cost c fuel , energy storage operation and maintenance cost c om.bat , energy storage charge and discharge efficiency η, energy storage power upper limit SOC max , energy storage power lower limit SOC min , and tie line upper limit P grid.max .

[0060] S2, calculate the energy storage discharge depth and linearize the function to obtain the energy storage life loss cost at different discharge depths of the energy storage, including the following steps:

[0061] S2.1, divide 100% discharge depth into 5 segments on average, calculate the discharge depth at time t of the energy storage, and determine the charge and discharge state coefficient, specifically as follows:

[0062]

[0063]

[0064] wherein, g d (t) is the charge-discharge state coefficient of the energy storage at the dth discharge depth, if the discharge depth of the energy storage at time t is located in the dth discharge depth, then the charge-discharge state coefficient of the energy storage at the dth discharge depth g d (t) = 1, otherwise g d (t) = 0, 1≤d≤5; SOC(t) represents the state of charge of the energy storage at time t; d d (t) represents the dth discharge depth of the energy storage at time t; dod d respectively represent the upper and lower limits of the dth discharge depth; g d (t) is the charge-discharge state coefficient of the energy storage at the dth discharge depth;

[0065] S2.2, according to the charge-discharge state coefficient, linearizing the minimum value for different discharge depth intervals according to the exponential function formula, determining the linearization coefficient K d , B d of the energy storage at the dth discharge depth, specifically as follows:

[0066] kpand kfare determined by the type of energy storage, in an embodiment, kpand kftake 1.31 and 1.28 respectively;

[0067] S2.3, linearizing the cycle count variable S bat (t) of the energy storage at time t, specifically as follows:

[0068]

[0069] wherein, U bat (t) = 0 indicates that the energy storage is discharging, U bat (t) = 1 indicates that the energy storage is charging;

[0070] S2.4, according to the linearization coefficient K d , B d of the energy storage at the dth discharge depth and the cycle count variable S bat (t) at time t, calculating the life consumption cost C bat of the energy storage, specifically as follows:

[0071]

[0072] wherein, M represents a very large number, in an embodiment, taking the value of 10000.

[0073] S3, establishing a micro-grid economic dispatching model with the minimum micro-grid daily operation cost as the target, the micro-grid daily operation cost including the life consumption cost of the energy storage, the cost of purchasing and selling electricity, the operation and maintenance cost of each unit and the fuel cost;

[0074] The objective function of the micro-grid economic dispatching model is expressed as follows:

[0075] minC=min{C ope} (1)

[0076] C ope =C grid +C om +C fuel +C bat (2)

[0077]

[0078] Wherein, C is the comprehensive operation cost of the micro-grid; C ope is the daily operation cost of the micro-grid; p is the discount rate, r is the discount years, C grid , C om and C fuel are the purchase and sale electricity cost, operation and maintenance cost of each unit and fuel cost, respectively, c grid (t) is the electricity price of the grid at time t, c fuel is the unit cost of fuel; c om.W , c om.PV , c om.G , c om，bat are the operation and maintenance cost coefficients of the wind turbine, photovoltaic, gas turbine and energy storage, respectively; P buy (t), P sell (t) are the purchase and sale electricity power of the micro-grid at time t, respectively; P G (t), P W (t) and P PV (t) are the output power of the gas turbine, wind turbine and photovoltaic at time t, respectively; P ch (t), P dis (t) are the charging and discharging power of the energy storage at time t, respectively; and At is the time step.

[0079] Further, in step S3, the constraint conditions of the micro-grid economic dispatching model include gas turbine constraints, power grid purchase power constraints, energy storage power and energy constraints, and power balance constraints.

[0080] Further, the gas turbine constraints are as follows:

[0081] P G.min ≤P G (t)≤P G.max (4)

[0082] Wherein, P G.min , P G.max are the upper and lower limits of the micro gas turbine output, respectively, which are limited by the minimum load rate and rated power;

[0083] Microgrid power constraints, specifically as follows:

[0084]

[0085] Where, P buy (t) and P sell (t) are the purchase and sale power of the microgrid at time t, respectively; P grid.max is the upper limit of the interactive power of the tie line between the microgrid and the distribution network; U grid (t) is the purchase and sale state variable of the microgrid at time t, 1 represents purchase, and 0 represents sale.

[0086] The energy storage power constraints include energy storage charging and discharging power constraints and energy storage state of charge (SOC) constraints;

[0087] Energy storage charging and discharging power constraints, specifically as follows:

[0088]

[0089] P bat.max = μE bat.max (7)

[0090] Where, P dis (t) and P ch (t) are the discharging and charging power of the energy storage at time t, respectively; P bat.max is the upper limit of the energy storage charging and discharging power, and μ is a fixed proportional coefficient of the energy storage power upper limit and rated capacity E bat.max .

[0091] Energy storage state of charge (SOC) constraints, specifically as follows:

[0092]

[0093] Where, Δt is the time step, taken as 1h; E(0) is the initial energy of the energy storage, SOC max and SOC min are the upper and lower limits of the state of charge of the energy storage, respectively, and η is the charging and discharging efficiency of the energy storage.

[0094] Power balance constraints, specifically as follows:

[0095] P dis (t) - P ch (t) + P buy (t) - P sell (t) + P G (t) = 0 (10).

[0096] S4. Solve the model using the commercial solver CLPEX to obtain the discharge and charging power P of the energy storage system at time t in the microgrid. dis (t) and P ch (t), and the power purchased and sold by the microgrid at time t. buy (t), P sell (t). Develop energy storage charging / discharging strategies and power purchase strategies for the microgrid at time t;

[0097] In one embodiment, taking a microgrid with energy storage, wind turbines, and photovoltaics as an example, the specific input data is shown in Table 1.

[0098] Table 1. Example Setup Data

[0099]

[0100] In this embodiment, the peak electricity price period is 9:00-11:00 and 19:00-23:00, with an electricity price of RMB 1.35 / kWh. The off-peak electricity price period is 24:00-8:00 and 12:00-18:00, with electricity prices of RMB 0.48 / kWh and RMB 0.9 / kWh, respectively.

[0101] In this embodiment, the output and load parameters of the photovoltaic and wind turbines are as follows: Figure 2 As shown.

[0102] In this embodiment, as Figure 3 , Figure 4 As shown, considering the energy storage cycle life, the energy storage discharge depth decreases significantly from 0:00 to 5:00. During peak electricity consumption periods from 12:00 to 18:00, the energy storage discharges at peak electricity prices and does not discharge during normal times, achieving energy transfer. Charging occurs during periods of low electricity consumption from 19:00 to 24:00, reducing the microgrid's electricity purchase cost, decreasing the number of energy storage charge / discharge cycles, and lowering the microgrid cost from 4537 yuan to 43319 yuan / day, thus saving on the total operating cost of the microgrid. In summary, in this embodiment, considering the energy storage cycle life, the discharge and charging power P of the energy storage system was obtained. dis (t) and P ch (t), and the power purchased and sold by the microgrid at time t. buy (t), P sell (t) Formulating energy storage operation strategies and microgrid power purchase strategies can effectively reduce energy storage lifespan loss, reduce microgrid operating costs, and achieve economical operation and dispatch of microgrids.

[0103] The preferred embodiments of the present application disclosed above are only used to help understand the present application and core ideas. For those skilled in the art, according to the ideas of the present application, there will be changes in specific application scenarios and implementation operations, and the description should not be understood as limiting the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. A microgrid economic dispatch method considering energy storage cycle life, characterized in that, Includes the following steps: S1. Read local electrical data; the electrical data includes: peak and off-peak electricity prices, wind turbine and photovoltaic power output data, load data, and gas turbine output limit P. G.min Lower limit of gas turbine output P G.max Unit operation and maintenance cost of wind turbines (c) om.W The unit operation and maintenance cost of photovoltaic power is c om.PV Unit operation and maintenance cost of gas turbine c om.G Unit fuel cost c fuel Energy storage unit operation and maintenance cost c om.bat Energy storage charge / discharge efficiency η, and maximum energy storage capacity (SOC) max Energy storage capacity lower limit SOC min and the upper limit of the communication line P grid.max ; S2. Calculate the energy storage discharge depth and linearize the function to obtain the energy storage lifetime loss cost at different discharge depths; including the following steps: S2.1 Divide the 100% depth of discharge into 5 equal segments, calculate the depth of discharge at time t, and determine the charge / discharge state coefficient, as follows: Among them, g d (t) represents the state-of-charge coefficient of energy storage at the discharge depth of segment d. If the discharge depth of energy storage at time t is located in segment d, then the state-of-charge coefficient of energy storage at the discharge depth of segment d is g. d (t) = 1, otherwise g d (t) = 0, 1 ≤ d ≤ 5; SOC(t) represents the state of charge of the stored energy at time t; dod d (t) represents the discharge depth of the dth segment at time t of energy storage; come d , respectively, represent the upper and lower limits of the discharge depth in segment d; E(0) represents the initial energy storage capacity; P ch (t') represents the energy storage charging power at time t'; Δt is the time step. S2.

2. Based on the state of charge / discharge coefficient, the exponential function formula is linearized for the minimum value in different discharge depth intervals to determine the linearization coefficient K of the energy storage at the discharge depth in the d-th segment. d B d The details are as follows: kp and kd are determined by the type of energy storage; S2.3, Energy storage cycle count variable S at time t bat (t) linearization, as follows: Among them, U bat When (t) is 0, it indicates energy storage and discharge, U bat When (t) is 1, it indicates energy storage charging; S2.4, Based on the linearization coefficient K of the energy storage at the discharge depth in the d-th segment. d B d and the cycle count variable S at time t bat (t), calculate the energy storage lifetime loss cost C bat The details are as follows: Where M represents a very large number; S3. Establish a microgrid economic dispatch model with the goal of minimizing the daily operating cost of the microgrid. The daily operating cost of the microgrid includes the energy storage life loss cost, electricity purchase and sale cost, operation and maintenance cost of each unit, and fuel cost. S4. Solve the microgrid economic dispatch model, and formulate energy storage charging and discharging strategies and power purchase strategies for the microgrid based on the obtained model decision variables.

2. The microgrid economic dispatch method considering energy storage cycle life as described in claim 1, characterized in that, In step S3, the objective function of the microgrid economic dispatch model is expressed as follows: minC=min{C ope } (1) C ope =C grid +C om +C fuel +C bat (2) Where C represents the overall operating cost of the microgrid; C ope ρ is the daily operating cost of the microgrid; ρ is the discount rate, r is the number of discount years, and C is the daily operating cost of the microgrid. grid C om and C fuel These are the costs of purchasing and selling electricity, the operation and maintenance costs of each unit, and the fuel costs, respectively. grid (t) represents the electricity price at time t in the power grid, and c fuel For fuel unit cost; P buy (t), P sell (t) represents the purchased and sold power of the microgrid at time t, respectively; P G (t), P W (t) and P PV (t) represents the output power of the gas turbine, wind turbine, and photovoltaic system at time t, respectively; P ch (t), P dis (t) represents the energy storage charging and discharging power at time t; Δt is the time step.

3. The microgrid economic dispatch method considering energy storage cycle life as described in claim 1, characterized in that, In step S3, the constraints of the microgrid economic dispatch model include gas turbine constraints, distribution network power purchase constraints, energy storage power constraints, and power balance constraints.

4. The microgrid economic dispatch method considering energy storage cycle life as described in claim 3, characterized in that, Gas turbine constraints are as follows: P G.min ≤P G (t)≤P G.max (4) Among them, P G.min P G.max These are the upper and lower limits of the output of the micro gas turbine, respectively limited by its minimum load rate and rated power.

5. A microgrid economic dispatch method considering energy storage cycle life as described in claim 3, characterized in that, The power constraints of the microgrid are as follows: Among them, P buy (t), P sell (t) represents the purchased and sold power of the microgrid at time t, respectively; P grid.max U represents the upper limit of the interaction power of the tie line between the microgrid and the distribution network. grid (t) represents the state variable of the microgrid's power purchase and sale at time t, where 1 represents power purchase and 0 represents power sale.

6. A microgrid economic dispatch method considering energy storage cycle life as described in claim 3, characterized in that, Energy storage power constraints include energy storage charge and discharge power constraints and energy storage state of charge constraints; The energy storage charging and discharging power constraints are as follows: P bat.max =μE bat.max (7) Among them, P dis (t), P ch (t) represents the energy storage discharge and charging power at time t, respectively; P bat.max The upper limit of the energy storage charging and discharging power is μ, where μ is the upper limit of the energy storage charging and discharging power and the rated capacity E. bat.max A fixed proportionality coefficient; Energy storage state of charge constraints: Where Δt is the time step, taken as 1 hour; E(0) is the initial energy storage capacity, and SOC is the state of charge. max SOC min η represents the upper and lower limits of the state of charge of the energy storage, respectively, and η is the energy storage charging and discharging efficiency.

7. A microgrid economic dispatch method considering energy storage cycle life according to any one of claims 4 to 6, characterized in that, The power balance constraints are as follows: P dis (t)-P ch (t)+P buy (t)-P sell (t)+P G (t)=0 (10)。 8. A microgrid economic dispatch method considering energy storage cycle life as described in claim 7, characterized in that, In step S4, the model decision variables are solved using the commercial solver clpex, including: the discharge and charging power P of the energy storage system at time t. dis (t) and P ch (t), and the power purchased and sold by the microgrid at time t. buy (t), P sell (t).

Images