A method for calculating the capacity of a power energy storage system based on time-series production simulation

Abstract

The present invention discloses a method for calculating the capacity of a power energy storage system based on time-series production simulation, which predicts the load data of a regional power grid as well as the wind speed and light intensity data, forms a time-series load curve and calculates the hourly output of wind power and photovoltaic power at the same time; determines the new energy consumption capacity of the system under the unit loading sequence model; formulates two charge-discharge simulation strategies for the energy storage to cooperate with new energy consumption and peak regulation of the power system, determines the corresponding unit loading numbers during energy storage charging and discharging and calculates the state of charge of the energy storage; according to the unit loading sequence and the energy storage charge-discharge model, performs time-series production simulation on the power grid with a time-series production simulation strategy, obtains the upper and lower limit intervals of the energy storage capacity under these two operation strategies, and optimizes within this interval to determine the capacity corresponding to the minimum charge-discharge cost of the energy storage; the present invention can obtain the optimal capacity configuration result of the energy storage, and further provide a basis and reference for the planning of the energy storage capacity.

Description

Technical Field

[0001] The present invention relates to the field of power grid operation planning, and in particular to a method for calculating the capacity of a power energy storage system based on chronological production simulation. Background Art

[0002] With the development of the economy, environmental issues have received increasing attention. Developing new energy is an important measure to alleviate environmental pollution, address climate change, and ensure the sustainable development of the economic society. However, with the increasing scale of new energy grid connection, there is a huge contradiction between the development of new energy and the uncertainty and volatility of its power generation. At the same time, due to problems such as imperfect market mechanisms, unclear local consumption responsibilities, and insufficient flexibility of system power sources, the power system is facing serious new energy consumption problems. The energy storage system has the characteristics of fast charge and discharge response and chronological energy regulation, can increase the peak shaving and frequency modulation capabilities of the system, and can solve the existing new energy consumption problems.

[0003] Renewable energy has strong volatility and uncertainty, and at the same time, renewable energy also has strong chronological characteristics. When planning energy storage for a power grid containing renewable energy, it is difficult to accurately describe the chronological change characteristics of load, new energy output, and energy storage state of charge using the traditional stochastic production simulation method of power systems, and it is also difficult to reflect the flexible and diverse operation and dispatching strategies of the system. Therefore, it is very necessary to study an optimal energy storage capacity calculation method based on chronological production simulation and adaptable to the characteristics of a new energy power system. Summary of the Invention

[0004] The technical problem solved by the present invention: Overcome the deficiencies of the traditional production simulation method with the continuous load curve as the framework when planning a new energy power system, provide a method for calculating the capacity of a power energy storage system based on chronological production simulation, establish a chronological model of new energy and energy storage under the chronological production simulation framework, and at the same time, according to the positive and negative conditions of the net load of the power grid, in the operation mode of the energy storage participating in the coordination of new energy consumption and power grid peak shaving in the power grid, formulate the operation strategy of the energy storage in the production simulation process, simulate the state of charge of the energy storage in the two operation modes, and determine the upper and lower limits of the energy storage capacity according to the charge and discharge characteristics of the energy storage under the two operation strategies. Compared with the production simulation method that simulates the energy storage state with only one operation strategy, the method of the present invention can narrow the search range of the energy storage capacity in the energy storage capacity optimization process, can better reflect the change process of the energy storage state of charge in the actual power grid, and thus provide corresponding basis and reference for the planning problem of the energy storage capacity.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] Step 1. Predict the load data, wind speed data, and light intensity data of the regional power grid to form a time-series load curve, and calculate the hourly output of wind power and photovoltaic power at the same time, so as to determine the time series of grid load and new energy output in the production simulation:

[0007] Step 1.1. Predict and obtain the load situation of the regional power grid, including the grid load magnitude at each simulation time interval t, so as to form the time-series load curve of the power grid;

[0008] Step 1.2. Predict the wind speed data and light intensity data at each simulation time interval t within the scope of the regional power grid;

[0009] Step 1.3. Establish the time-series output models of wind power and photovoltaic power;

[0010] Use Equation (1) to establish the wind power output model as:

[0011]

[0012] In Equation (1): P w (t) is the output power of the fan at time t, V i , V o , V n are the cut-in wind speed, cut-out wind speed, and rated wind speed of the fan respectively, V t is the predicted wind speed magnitude at time t, P Wn is the rated power of the fan;

[0013] Use Equation (2) to establish the photovoltaic output model as:

[0014]

[0015] In Equation (2): P ph (t) is the output power of the photovoltaic at time t, P phn , γ n are the rated power of the photovoltaic and the rated light intensity respectively, γ t is the light intensity at time t.

[0016] Step 1.4. According to the wind speed data and light intensity data obtained in Step 1.2, substitute them into the wind power and photovoltaic output models in Step 1.3 respectively to obtain the time series of wind power and photovoltaic output.

[0017] Step 2. Considering the influence of the unit operation process and unit start-stop, establish a time-series production simulation unit loading sequence model. Considering the priority of new energy consumption, determine the unit sequence in standby state in the power grid when the new energy output cannot be consumed according to the unit loading sequence model. Obtain the sum of the minimum technical outputs of the standby units from the standby unit sequence, and at the same time, combine the grid load and new energy output time series obtained in Step 1 to determine the consumable power of new energy:

[0018] Step 2.1: Consider the impacts brought by the start-stop and operation processes of thermal power units on the unit production. Determine the loading sequence of thermal power units with the goal of minimizing the operation cost during unit start-stop. The objective function considering the start-stop and operation costs of thermal power units is shown in Equation (3):

[0019]

[0020] In Equation (3): t is the simulation time interval, T is the total simulation time length, n represents the nth thermal power unit, N is the total number of thermal power units, C n (t) is the operation cost of the nth thermal power unit at time t, K on (t) and K off (t) are 0, 1 variables representing the start-up and shutdown states of the thermal power unit at time t respectively, C non and C noff represent the start-up and shutdown costs of the nth thermal power unit respectively;

[0021] According to the above objective function, determine the loading sequence of units in the power grid during each simulation period as {G1, G2, … G s} t , where s is the number of units loaded during each simulation period.

[0022] Step 2.2: Consider the problem of new energy consumption. When the predicted output of new energy at time t is greater than the predicted value of the current power grid load, according to the unit loading sequence obtained in Step 2.1, determine the loading sequence of system hot standby units at time t as {b1, b2, …, b k} t , where k is the number of units in hot standby in the power grid at time t. Thus, calculate the sum of the minimum technical outputs of the hot standby loaded units at time t as shown in Equation (4):

[0023]

[0024] In Equation (4), P Gmin (t) is the sum of the minimum technical outputs of the hot standby units at time t, and P Gmini (t) is the minimum technical output of the ith hot standby unit at time t;

[0025] Step 2.3: Superimpose the negative value of the predicted output of new energy and the predicted load of the current power grid to obtain the net load of the current power grid as shown in Equation (5):

[0026] P lj (t) = -P e (t) + P l (t) (5)

[0027] In Equation (5): P lj (t) is the system net load at time t, and P l (t) is the predicted system load at time t, and P e (t) is the predicted output value of new energy at time t;

[0028] Step 2.4: When the predicted output of new energy at time t is greater than the predicted load value at this time, according to the sum of the minimum technical output of the thermal standby units at time t obtained in Step 2.2 and the system net load at this time obtained in Step 2.3, the consumable power of the new energy output at time t is obtained as shown in Equation (6):

[0029] P x (t) = P lj (t) + P e (t) - P Gmin (t) (6)

[0030] In Equation (6): P x (t) is the consumable power of new energy at time t.

[0031] Step Three: Respectively formulate the charge and discharge strategies for energy storage to cooperate with the consumption of new energy during the production simulation process and the charge and discharge strategies for peak shaving of the power system. Considering the priority consumption of new energy using the unit loading sequence model obtained in Step Two, calculate the charge and discharge power of energy storage and the state of charge of energy storage:

[0032] Step 3.1: When the predicted output of new energy is greater than the predicted load value, calculate the non-consumable amount of new energy output as shown in Equation (7):

[0033] P d (t) = P Gmin (t) - P lj (t) (7)

[0034] In Equation (7): P d (t) is the non-consumable amount of new energy output at time t;

[0035] Step 3.2: At the moment when the predicted output of new energy is greater than the predicted load value, adopt the strategy of preferentially consuming new energy for energy storage. First, use the non-consumable amount of new energy obtained in Step 3.1 to charge energy storage. The charging power of energy storage is as shown in Equation (8):

[0036] P c1 (t) = min(P d (t), P cmax ) (8)

[0037] In Equation (8): P c1 (t) is the charging power of energy storage under the strategy of promoting the consumption of new energy, and P cmaxis the maximum charging power of the energy storage;

[0038] Step 3.3: When the predicted output of new energy is less than the predicted load value, the energy storage adopts a charge-discharge strategy to cooperate with the power grid for peak regulation for production simulation:

[0039] Load the units one by one according to the unit loading sequence described in Step 2.1. When the available capacity of the current K c th loaded unit exceeds the current grid net load, the energy storage reaches the charging condition. At this time, the number of loaded units K c is the number of loaded units when the energy storage reaches the charging condition, as shown in Equation (9):

[0040] P kc (t) > P lj (t) (9)

[0041] In Equation (9): P kc (t) is the available generating capacity of the first K c loaded units;

[0042] After the energy storage is charged, calculate the charging power of the energy storage according to Equation (10):

[0043]

[0044] In Equation (10): P c2 (t) is the charging power of the energy storage under the peak regulation strategy of the power grid, SOC max is the maximum state of charge of the energy storage, SOC t-1 is the state of charge of the energy storage at the previous moment, △t is the simulation time interval, η c is the charging efficiency of the energy storage, and E is the rated capacity of the energy storage;

[0045] When the sum of the outputs of the current K f units is less than the current system net load, and the sum of the outputs of the units after loading the K f +1th unit is greater than the system net load, the energy storage reaches the discharging condition. At this time, the number of loaded units K f is the number of loaded units when the energy storage reaches the discharging condition, as shown in Equation (11):

[0046]

[0047] In Equation (11): P kf (t) is the available generating capacity of the first K f loaded units, and P kf+1 (t) is the available generating capacity of the first K f +1th loaded unit;

[0048] After the energy storage is discharged, calculate the discharging power of the energy storage according to Equation (12):

[0049]

[0050] In formula (12): P f (t) is the energy storage discharge power, and SOC min is the minimum state of charge of the energy storage, and η f is the energy storage discharge efficiency, and P fmax is the maximum discharge power of the energy storage;

[0051] Step 3.4: After obtaining the energy storage charge and discharge power by simulating and calculating using the two energy storage production simulation strategies in Steps 3.2 and 3.3, update the state of charge after the energy storage charging is completed according to formula (13):

[0052]

[0053] In formula (13): SOC t is the state of charge of the energy storage at time t, and SOC t-1 is the state of charge of the energy storage at time t - 1, and P c (t - 1) is the charging power of the energy storage at time t - 1;

[0054] Update the state of charge after the energy storage discharge is completed according to formula (14):

[0055]

[0056] In formula (14): P f (t - 1) is the discharge power of the energy storage at time t - 1;

[0057] Step Four: Considering the operation mode of the energy storage obtained in Step Three, which is to absorb new energy output and participate in power grid peak regulation, determine the upper and lower limits of the energy storage capacity, and optimize to obtain the optimal energy storage capacity configuration within the upper and lower limit intervals of the energy storage capacity through production simulation:

[0058] Step 4.1: Set the maximum state of charge of the energy storage during production simulation as SOC max , the minimum state of charge as SOC min , and the initial state of charge as SOC0;

[0059] Step 4.2: Considering both the operation strategies of the energy storage to preferentially absorb new energy and participate in power grid peak regulation, determine the lower limit value of the energy storage capacity according to formula (15) and the upper limit value of the energy storage capacity according to formula (16):

[0060]

[0061]

[0062] In formulas (15) and (16): Emin and E max are the lower and upper limits of the energy storage capacity respectively; S x , S c and S f are both 0,1 variables, S x being 1 indicates that the energy storage participates in the new energy consumption at this time, S c being 1 indicates that the energy storage participates in the power grid peak regulation and is in the charging state, S f being 1 indicates that the energy storage participates in the power grid peak regulation and is in the discharging state; σ is the prediction error between the new energy and the load;

[0063] Step 4.3. Select the energy storage capacity within the upper and lower limits of the energy storage capacity determined in Step 4.2 to calculate the operation cost of the energy storage as shown in Equation (17):

[0064] C = (μ e + μ w )E0 + μ p P n (17)

[0065] In Equation (17): μ e , μ w and μ p are the unit capacity coefficient of the energy storage, the unit capacity operation and maintenance coefficient, and the unit power coefficient respectively, P n is the rated charge and discharge power of the energy storage;

[0066] Step 4.4. Set the step size of the energy storage capacity change △E, and update the capacity of the energy storage within the upper and lower limits of the energy storage capacity in the next production simulation as shown in Equation (18):

[0067] E n0 = E (n-1)0 + △E (18)

[0068] In Equation (18): E n0 is the initial capacity of the energy storage in the nth production simulation system, E (n-1)0 is the initial capacity of the energy storage in the (n - 1)th production simulation system;

[0069] Step 4.5. Consider the operation constraints of the energy storage as shown in Equation (19):

[0070]

[0071] In Equation (19), D c and D f are 0,1 variables, representing the charging and discharging states of the energy storage respectively;

[0072] The capacity of the energy storage satisfies the constraint:

[0073] E min < En0 <E max (20)

[0074] Using the energy storage related state of charge determined in step 4.1, considering the above two energy storage constraints, perform a chronological production simulation on the power system with new energy and energy storage. Use the method described in step 4.2 to determine the upper and lower limit intervals of the energy storage capacity based on the production simulation results. Update the energy storage capacity within this interval, and use step 4.3 to calculate the production cost of the energy storage, and find the energy storage capacity corresponding to the minimum production cost of the energy storage.

[0075] Compared with the existing technologies, the beneficial effects of the present invention are reflected in:

[0076] Compared with the existing traditional power system production simulation method, the method of the present invention overcomes the problem that the traditional production simulation method with a continuous load curve as the framework is difficult to reflect the chronological characteristics of new energy and energy storage. With the chronological load curve as the framework, it simulates the time series of new energy output and the state of charge of energy storage, so as to correspond the operation scheduling strategy with the loading order of each unit and the charge and discharge conditions of energy storage on the time scale. At the same time, according to the positive and negative conditions of the net load of the power grid, with the operation mode of the energy storage participating in the coordinated operation of new energy consumption and power grid peak shaving in the power grid, formulate the operation strategy of the energy storage in the production simulation process, simulate the state of charge of the energy storage in the two operation modes, and determine the upper and lower limit values of the energy storage capacity according to the charge and discharge characteristics of the energy storage under the two operation strategies. Compared with the production simulation method that simulates the energy storage state with only one operation strategy, the method of the present invention can narrow the search range of the energy storage capacity in the energy storage capacity optimization process, can better reflect the change process of the state of charge of the energy storage in the actual power grid, and thus provide corresponding basis and reference for the planning problem of the energy storage capacity. Brief Description of the Drawings

[0077] Figure 1 It is a schematic flow chart of the power energy storage system capacity calculation method based on chronological production simulation of the present invention. Detailed Embodiment

[0078] To have a further understanding and recognition of the structural features and achieved effects of the present invention, the following is a detailed description with the help of preferred embodiments and accompanying drawings:

[0079] As Figure 1 shown, a power energy storage system capacity calculation method based on chronological production simulation of the present invention includes the following steps:

[0080] Step 1: Predict the load data of the regional power grid, as well as the wind speed and light data, form a chronological load curve, and calculate the hourly output of wind power and photovoltaic power at the same time, so as to determine the time series of the power grid load and new energy output in the production simulation:

[0081] Step 1.1. Predict the load condition of the regional power grid, including the grid load magnitude at each simulation time interval t, and form a time-series load curve of the power grid accordingly.

[0082] Step 1.2. Predict the wind speed data and light intensity data at each simulation time interval t within the scope of the regional power grid.

[0083] Step 1.3. Establish a time-series output model for wind power and photovoltaic power.

[0084] Use Equation (1) to establish the wind power output model as:

[0085]

[0086] In Equation (1): P w (t) is the output power of the wind turbine at time t, V i , V o , V n are the cut-in wind speed, cut-out wind speed and rated wind speed of the wind turbine respectively, V t is the predicted wind speed magnitude at time t, P Wn is the rated power of the wind turbine;

[0087] Use Equation (2) to establish the photovoltaic power output model as:

[0088]

[0089] In Equation (2): P ph (t) is the output power of the photovoltaic at time t, P phn , γ n are the rated power of the photovoltaic and the rated light intensity respectively, γ t is the light intensity at time t.

[0090] Step 1.4. According to the wind speed data and light intensity data obtained in Step 1.2, substitute them into the wind power and photovoltaic power output models in Step 1.3 respectively to obtain the time series of wind power and photovoltaic power output.

[0091] Step Two. Consider the influence of the unit operation process and unit start-stop, establish a time-series production simulation unit loading sequence model, consider the priority of new energy consumption, and determine the unit sequence in standby state in the power grid when the new energy output cannot be consumed according to the unit loading sequence model. Obtain the sum of the minimum technical outputs of the standby units from the standby unit sequence, and at the same time, combine the power grid load and new energy output time series obtained in Step One to determine the consumable power of the new energy:

[0092] When considering the impact of unit operation process and start-stop, optimization should be carried out with all power sources within the optimization cycle as the goal. However, considering that the start-stop cost of hydropower units is very small compared to thermal power units, the present invention only considers thermal power units when considering the impact of unit operation and start-stop.

[0093] Step 2.1: Consider the impact of unit start-stop and unit operation process on unit production during the operation of thermal power units. Determine the loading sequence of thermal power units with the goal of minimizing the operation cost according to unit start-stop. The objective function considering the start-stop and operation cost of thermal power units is shown in Equation (3):

[0094]

[0095] In Equation (3): t is the simulation time interval, T is the total simulation time length, n represents the nth thermal power unit, N is the total number of thermal power units, C n (t) is the operation cost of the nth thermal power unit at time t, K on (t) and K off (t) are 0, 1 variables representing the start-up and shutdown states of the thermal power unit at time t respectively, C non and C noff represent the start-up and shutdown costs of the nth thermal power unit respectively;

[0096] According to the above objective function, determine the loading sequence of units in the power grid during each simulation period as {G1, G2, … G s} t , where s is the number of units loaded during each simulation period.

[0097] Step 2.2: Consider the problem of new energy consumption. When the predicted output of new energy at time t is greater than the predicted value of the current power grid load, according to the unit loading sequence obtained in Step 2.1, determine the loading sequence of system hot standby units at time t as {b1, b2, …, b k} t , where k is the number of units in hot standby in the power grid at time t. Thus, calculate the sum of the minimum technical outputs of the hot standby loading units at time t as shown in Equation (4):

[0098]

[0099] In Equation (4), P Gmin (t) is the sum of the minimum technical outputs of the hot standby units at time t, and P Gmini (t) is the minimum technical output of the ith hot standby unit at time t;

[0100] Step 2.3: Superimpose the negative value of the predicted output of new energy and the predicted load of the current power grid to obtain the net load of the current power grid as shown in Equation (5):

[0101] P lj P(t) = -P e (t) + P l (t) (5)

[0102] In Equation (5): P lj (t) is the system net load at time t, P l (t) is the predicted system load at time t, P e (t) is the predicted output value of new energy at time t;

[0103] Step 2.4: When the predicted output of new energy at time t is greater than the predicted load value at this time, according to the sum of the minimum technical output of the thermal reserve units at time t obtained in Step 2.2 and the system net load at this time obtained in Step 2.3, the consumable power of the new energy output at time t is obtained as shown in Equation (6):

[0104] P x (t) = P lj (t) + P e (t) - P Gmin (t) (6)

[0105] In Equation (6): P x (t) is the consumable power of new energy at time t.

[0106] Step Three: Respectively formulate the charge and discharge strategies for energy storage to cooperate with the consumption of new energy during the production simulation process and the charge and discharge strategies for peak shaving of the power system. Considering the priority consumption of new energy using the unit loading sequence model obtained in Step Two, calculate the charge and discharge power of energy storage and the state of charge of energy storage:

[0107] Energy storage is a relatively special component in the power system. When the operating conditions reach the discharge condition, it switches to the discharge state, equivalent to the output power of a generator set, and when the charging condition is met, it can switch to the charging state, equivalent to an adjustable load absorbing electrical energy from the system. The back-and-forth switching of energy storage between the charge and discharge states brings new problems to the system time-series production simulation. Therefore, the present invention treats the charge and discharge states of energy storage as a load and a generator set respectively.

[0108] Step 3.1: When the predicted output of new energy is greater than the predicted load value, calculate the non-consumable amount of new energy output as shown in Equation (7):

[0109] P d (t) = P Gmin (t) - P lj (t) (7)

[0110] In Equation (7): P d (t) is the non-consumable amount of new energy output at time t;

[0111] Step 3.2. At the moment when the predicted output of new energy is greater than the predicted load value, adopt the strategy of preferentially consuming new energy for energy storage, and preferentially use the amount of unconsumed new energy obtained in Step 3.1 to charge the energy storage. The charging power of the energy storage is as shown in Equation (8):

[0112] P c1 (t) = min(P d (t), P cmax ) (8)

[0113] In Equation (8): P c1 (t) is the charging power of the energy storage under the strategy of promoting the consumption of new energy, and P cmax is the maximum charging power of the energy storage;

[0114] Step 3.3. In the case where the predicted output of new energy is less than the predicted load value, adopt the charge and discharge strategy of the energy storage cooperating with the power grid peak regulation for production simulation:

[0115] Load the units one by one according to the unit loading sequence described in Step 2.1. When the available capacity of the current K c th loaded unit exceeds the current power grid net load, the energy storage reaches the charging condition. At this time, the number of loaded units K c is the number of loaded units when the energy storage reaches the charging condition, as shown in Equation (9):

[0116] P kc (t) > P lj (t) (9)

[0117] In Equation (9): P kc (t) is the available generating capacity of the first K c loaded units;

[0118] After the energy storage is charged, calculate the charging power of the energy storage according to Equation (10):

[0119]

[0120] In Equation (10): P c2 (t) is the charging power of the energy storage under the strategy of cooperating with the power grid peak regulation, SOC max is the maximum state of charge of the energy storage, SOC t-1 is the state of charge of the energy storage at the previous moment, △t is the simulation time interval, η c is the charging efficiency of the energy storage, and E is the rated capacity of the energy storage;

[0121] When the sum of the outputs of the current K f units is less than the current system net load, and K fWhen the sum of the unit outputs after +1 unit is loaded is greater than the system net load, the energy storage reaches the discharge condition. At this time, the number of loaded units K f is the number of loaded units when the energy storage reaches the discharge condition, as shown in Equation (11):

[0122]

[0123] In Equation (11): P kf (t) is the available generating capacity of the first K f loaded units, and P kf+1 (t) is the available generating capacity of the first K f +1 loaded units;

[0124] After the energy storage discharges, calculate the discharge power of the energy storage according to Equation (12):

[0125]

[0126] In Equation (12): P f (t) is the discharge power of the energy storage, SOC min is the minimum state of charge of the energy storage, η f is the discharge efficiency of the energy storage, and P fmax is the maximum discharge power of the energy storage;

[0127] Step 3.4. After obtaining the charge and discharge powers of the energy storage by simulating and calculating using the two energy storage production simulation strategies in Steps 3.2 and 3.3, update the state of charge after the energy storage is charged according to Equation (13):

[0128]

[0129] In Equation (13): SOC t is the state of charge of the energy storage at time t, SOC t-1 is the state of charge of the energy storage at time t-1, and P c (t-1) is the charging power of the energy storage at time t-1;

[0130] Update the state of charge after the energy storage discharges according to Equation (14):

[0131]

[0132] In Equation (14): P f (t-1) is the discharge power of the energy storage at time t-1;

[0133] Step Four. Considering the operation mode of the energy storage obtained in Step Three, which is to absorb new energy output and participate in power grid peak regulation, determine the upper and lower limits of the energy storage capacity, and find the optimal capacity configuration of the energy storage by optimizing within the upper and lower limit range of the energy storage capacity through production simulation:

[0134] Step 4.1: Set the maximum state of charge of the energy storage during production simulation as SOC max , the minimum state of charge as SOC min , and the initial state of charge as SOC0;

[0135] Step 4.2: Considering both the operation strategies of giving priority to the consumption of new energy by the energy storage and participating in grid peak shaving, determine the lower limit value of the energy storage capacity according to Equation (15) and the upper limit value of the energy storage capacity according to Equation (16):

[0136]

[0137]

[0138] In Equation (15) and Equation (16): E min and E max are the lower limit and upper limit of the energy storage capacity respectively; S x , S c and S f are all 0, 1 variables. S x being 1 indicates that the energy storage participates in the consumption of new energy at this time, S c being 1 indicates that the energy storage participates in grid peak shaving and is in the charging state, and S f being 1 indicates that the energy storage participates in grid peak shaving and is in the discharging state; σ is the prediction error of new energy and load;

[0139] Step 4.3: Select the energy storage capacity from the upper and lower limits of the energy storage capacity determined in Step 4.2 and calculate the operation cost of the energy storage as Equation (17):

[0140] C = (μ e + μ w )E0 + μ p P n (17)

[0141] In Equation (17): μ e , μ w and μ p are the unit capacity coefficient, unit capacity operation and maintenance coefficient, and unit power coefficient of the energy storage respectively, and P n is the rated charge-discharge power of the energy storage;

[0142] Step 4.4: Set the step size of the energy storage capacity change as △E, and update the capacity of the energy storage in the interval of the upper and lower limits of the energy storage capacity during the next production simulation as shown in Equation (18):

[0143] E n0 = E (n-1)0 + △E (18)

[0144] In Equation (18): E n0is the initial capacity of energy storage in the nth production simulation system, E (n-1)0 is the initial capacity of energy storage in the (n - 1)th production simulation system;

[0145] Step 4.5: Consider the energy storage operation constraints as shown in Equation (19):

[0146]

[0147] In Equation (19), D c and D f are binary variables, representing the charging and discharging states of the energy storage respectively;

[0148] The capacity of the energy storage satisfies the constraints:

[0149] E min < E n0 < E max (20)

[0150] Using the state of charge of the energy storage determined in Step 4.1, consider the above two energy storage constraints to conduct a chronological production simulation on the power system with new energy and energy storage. Use the method described in Step 4.2 to determine the upper and lower limit intervals of the energy storage capacity based on the production simulation results. Update the capacity of the energy storage within this interval, calculate the production cost of the energy storage using Step 4.3, and find the energy storage capacity corresponding to the minimum production cost of the energy storage.

[0151] Further explanation of Step Four:

[0152] The idea of simulating the time series of the state of charge of the energy storage is as follows: When the predicted output of new energy is greater than the predicted load value, the energy storage charges to absorb the output of new energy. At this time, the energy storage mainly cooperates with new energy. When the predicted output of new energy is less than the predicted load value, first load the units according to the unit loading sequence determined in Step Two to meet the load, and then use the energy storage to shave peaks and fill valleys to regulate the peak of the system. At this time, the energy storage mainly cooperates with the grid dispatching operation. Repeat the simulation of the charging and discharging states of the energy storage according to the above two situations at each simulation time interval to obtain the upper and lower limit intervals of the energy storage capacity. Set an energy storage capacity within this interval. When the production simulation duration is reached, the simulation ends, and the state of charge of the energy storage and the charging and discharging cost of the energy storage within the simulation period under the scenario of this specific energy storage capacity are obtained. Then, through an optimization method, different energy storage capacities are selected within the upper and lower limit intervals of the energy storage capacity to simulate the charging and discharging costs of the energy storage under different energy storage capacity scenarios, and the energy storage capacity corresponding to the minimum cost is obtained.

[0153] Although the specific implementation methods of the present invention are described above, those skilled in the art should understand that these are only examples. Without departing from the principles and implementation of the present invention, various changes or modifications can be made to these implementation schemes. Therefore, the protection scope of the present invention is defined by the appended claims.

Claims

1. A method for calculating the capacity of a power energy storage system based on time-series production simulation, characterized in that It includes the following steps: Step 1: Predict the load data, wind speed data, and light intensity data of the regional power grid, form a time-series load curve, and calculate the hourly output of wind power and photovoltaic power at the same time, so as to determine the time series of the power grid load and new energy output in the production simulation, and provide a basis for formulating the energy storage operation strategy in the subsequent steps; Step 2: Considering the influence of the unit operation process and unit start-stop, establish a time-series production simulation unit loading sequence model, considering the priority of new energy consumption. Use the unit loading sequence model to determine the unit sequence in standby state in the power grid when the new energy output cannot be consumed, obtain the sum of the minimum technical outputs of the standby units from the standby unit sequence, and at the same time combine the power grid load and new energy output time series obtained in Step 1 to determine the consumable power of new energy; Step 3: Respectively formulate the charge and discharge strategies for energy storage to cooperate with new energy consumption during the production simulation process and the charge and discharge strategies for peak shaving of the power system. Use the unit loading sequence model obtained in Step 2 to determine the number of loaded units corresponding to the energy storage charge and discharge, calculate the energy storage charge and discharge power and the state of charge of the energy storage; Step 4: Based on the dual-strategy operation mode of energy storage to consume new energy output and participate in power grid peak shaving obtained in Step 3, determine the upper and lower limits of the energy storage capacity, and find the optimal capacity configuration of the energy storage by optimizing within the interval of the upper and lower limits of the energy storage capacity through production simulation.

2. The method for calculating the capacity of a power energy storage system based on sequential production simulation according to claim 1, wherein: The specific implementation of Step 1 is as follows: Step 1.1: Obtain the predicted load data of the regional power grid. The load data includes the power grid load magnitude at each simulation time interval t, and thus form the time-series load curve of the power grid; Step 1.2: Predict the wind speed data and light intensity data at each simulation time interval t within the scope of the regional power grid; Step 1.3: Establish a time-series output model for wind power and photovoltaic power; Use Equation (1) to establish the wind power output model as: (1) In formula (1): is the output power of the wind turbine at time t, , , are the cut-in wind speed, cut-out wind speed and rated wind speed of the wind turbine respectively, is the predicted wind speed magnitude at time t, is the rated power of the wind turbine; Use Equation (2) to establish the photovoltaic power output model as: (2) In formula (2): is the output power of the photovoltaic at time t, , are the rated power and rated light intensity of the photovoltaic respectively, is the light intensity at time t; Step 1.4: According to the wind speed data and light intensity data obtained in Step 1.2, substitute them into the wind power and photovoltaic power output models in Step 1.3 respectively to obtain the time series of wind power and photovoltaic power output.

3. The method for calculating the capacity of a power energy storage system based on sequential production simulation according to claim 1, wherein: The specific implementation of Step 2 is as follows: Step 2.1: Considering the influence of thermal power unit start-stop and unit operation process on unit production, determine the loading sequence of thermal power units with the goal of minimizing the start-stop and operation costs of the units. The objective function considering the start-stop and operation costs of thermal power units is shown in Equation (3): (3) In Equation (3): t is the simulation time interval, T is the total simulation time length, n represents the nth thermal power unit, and N is the total number of thermal power units. is the operating cost of the nth thermal power unit at time t. and are 0, 1 variables representing the start-up and shutdown states of the thermal power unit at time t, respectively. and represent the start-up and shutdown costs of the nth thermal power unit, respectively. According to the above objective function, determine the loading sequence of the units in the power grid for each simulation period as , where s is the number of units loaded in each simulation period; Step 2.

2. Considering the problem of new energy consumption, when the predicted output of new energy at time t is greater than the predicted value of the grid load at the current moment, according to the unit loading sequence obtained in Step 2.1, determine the system hot standby unit loading sequence at time t as , where k is the number of units in hot standby in the grid at time t, and the sum of the minimum technical outputs of the hot standby loading units at time t is calculated as shown in Equation (4): (4) In formula (4) is the sum of the minimum technical outputs of the hot standby units at time t, is the minimum technical output of the i-th hot standby unit at time t; Step 2.3: Superimpose the negative value of the predicted new energy output and the predicted power grid load magnitude at the current moment to obtain the net load magnitude of the power grid at the current moment as shown in Equation (5): (5) In formula (5): is the magnitude of the system net load at time t, is the predicted magnitude of the system load at time t, is the predicted output value of new energy at time t; Step 2.4: When the predicted new energy output at time t is greater than the predicted load value at that time, according to the sum of the minimum technical outputs of the thermal standby units at time t obtained in Step 2.2 and the net load magnitude of the power grid at that time obtained in Step 2.3, obtain the consumable power of the new energy output at time t as shown in Equation (6): (6) In formula (6): is the consumption power of new energy at time t.

4. The method for calculating the capacity of a power energy storage system based on sequential production simulation according to claim 3, wherein: The specific implementation of Step 3 is as follows: Step 3.1: When the predicted new energy output is greater than the predicted load value, calculate the unconsumable amount of the new energy output as shown in Equation (7): (7) In formula (7): is the amount of new energy output that cannot be absorbed at time t; Step 3.

2. At the moment when the predicted output of new energy is greater than the load prediction value, adopt the strategy of preferentially consuming new energy by energy storage, and use the amount of unconsumable new energy obtained in Step 3.1 to charge the energy storage. The charging power of the energy storage is shown in Equation (8): (8) In Equation (8): is the charging power of the energy storage under the strategy of promoting the accommodation of new energy, is the maximum charging power of the energy storage; Step 3.

3. In the case where the predicted output of new energy is less than the load prediction value, adopt the charge and discharge strategy of the energy storage cooperating with the power grid peak regulation for production simulation: Load the units one by one according to the unit loading sequence described in Step 2.

1. When the available capacity of the currently kc loaded units exceeds the current grid net load, the energy storage reaches the charging condition. At this time, the number of loaded units kc is the number of loaded units when the energy storage reaches the charging condition, as shown in Equation (9): (9) In formula (9): is the available generating capacity of the first kc loading units; After the energy storage is charged, calculate the charging power of the energy storage according to Equation (10): (10) In formula (10): is the charging power of the energy storage under the strategy of coordinating with the power grid for peak shaving, is the maximum state of charge of the energy storage, is the state of charge of the energy storage at time t-1, is the simulation time interval, is the charging efficiency of the energy storage, is the energy storage capacity; When the sum of the outputs of the currently kf units is less than the current system net load, and the sum of the outputs of the units after the kf + 1th unit is loaded is greater than the system net load, the energy storage reaches the discharging condition. At this time, the number of loaded units kf is the number of loaded units when the energy storage reaches the discharging condition, as shown in Equation (11): (11) In formula (11): is the available power generation capacity of the first kf loading units, is the available power generation capacity of the first kf + 1 loading units; After the energy storage is discharged, calculate the discharging power of the energy storage according to Equation (12): (12) In formula (12): is the energy storage discharge power, is the minimum state of charge of the energy storage, is the energy storage discharge efficiency, is the maximum discharge power of the energy storage; Step 3.

4. After adopting the two energy storage production simulation strategies in Step 3.2 and Step 3.3 to simulate and calculate the charge and discharge power of the energy storage, update the state of charge after the energy storage is charged according to Equation (13): (13) In formula (13): is the state of charge of the energy storage at time t, is the state of charge of the energy storage at time t-1, is the charging power of the energy storage at time t-1; Update the state of charge after the energy storage is discharged according to Equation (14): (14) In formula (14): is the discharge power of energy storage at time t-1.

5. The method for calculating the capacity of a power energy storage system based on time-series production simulation according to claim 4, wherein: The specific implementation of Step 4 is as follows: Step 4.1: Set the maximum state of charge of the energy storage during production simulation to be , the minimum state of charge to be , and the initial state of charge to be ; Step 4.

2. Considering both the operation strategies of the energy storage for preferentially consuming new energy and participating in the power grid peak regulation, determine the lower limit value of the energy storage capacity according to Equation (15) and the upper limit value of the energy storage capacity according to Equation (16): (15) (16) In Formula (15) and Formula (16): and are respectively the lower limit and the upper limit of the energy storage capacity; , and are both 0,1 variables, being 1 indicates that the energy storage participates in new energy consumption at this time, being 1 indicates that the energy storage participates in power grid peak shaving and is in the charging state, being 1 indicates that the energy storage participates in power grid peak shaving and is in the discharging state; is the prediction error between new energy and load; Step 4.

3. Select the energy storage capacity from the upper and lower limits of the energy storage capacity determined in Step 4.2, and calculate the operation cost of the energy storage as shown in Equation (17): (17) In formula (17): , and are the energy storage unit capacity coefficient, the unit capacity operation and maintenance coefficient, and the unit power coefficient respectively, is the rated charge and discharge power of the energy storage; Step 4.

4. Set the step size of the energy storage capacity change , and update the energy storage capacity within the upper and lower limits of the energy storage capacity during the next production simulation as shown in Equation (18): (18) In formula (18): is the initial capacity of energy storage in the nth production simulation system, is the initial capacity of energy storage in the (n - 1)th production simulation system; Step 4.

5. Consider the energy storage operation constraints as shown in Equation (19): (19) D in Equation (19) c and D f are 0, 1 variables, representing the charging and discharging states of the energy storage, respectively; The capacity of the energy storage meets the constraints: (20) Using the state of charge of the energy storage determined in Step 4.1, considering the above two energy storage constraints, perform time-series production simulation on the power system containing new energy and energy storage. Based on the method in Step 4.2, determine the upper and lower limit intervals of the energy storage capacity using the production simulation results. Update the capacity of the energy storage within this interval, calculate the production cost of the energy storage using Step 4.3, and find the energy storage capacity corresponding to the minimum production cost of the energy storage.

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