Wind and light energy storage optimization method and system for low-carbon economic park

Abstract

The invention relates to the technical field of wind and light energy storage, in particular to a wind and light energy storage optimization method and system for a low-carbon economic park. Comprising the steps that a plurality of energy storage sub-regions are established based on park parameters, an energy storage sub-region sequence A is generated, A = (a1, a2... an), and ai is the ith energy storage sub-region; n is the number of the energy storage sub-regions; establishing an energy storage collaborative model, and setting energy storage equipment parameters in each energy storage sub-region; according to a preset feedback time node, obtaining operation parameters of each energy storage sub-region, and judging whether a correction instruction is generated or not; according to the park parameters, a plurality of energy storage sub-regions are established, and corresponding energy storage modules are established for each energy storage sub-region, so that regional adjustment is carried out on the interior of the park, the normal power supply demand of the interior of the park in the valley period of wind and light power generation is ensured, and the peak clipping and valley filling optimization scheduling efficiency of a power system is improved. And the overall operation and maintenance cost of the energy storage system is reduced.

Description

Technical Field

[0001] The present application relates to the field of wind and solar energy storage technology, and in particular to a wind and solar energy storage optimization method and system for a low-carbon economic park. Background Art

[0002] In recent years, renewable energy represented by wind and solar has developed rapidly due to its green and environmentally friendly advantages. However, the output of wind and solar is random and volatile, which poses a great challenge to the frequency and voltage stability of the distribution network, and also interferes with the economic and reliable operation of the distribution network. Connecting energy storage equipment to the distribution network can effectively solve these problems. The battery energy storage system (BESS) composed of batteries has the characteristics of flexible installation, high energy density, and fast charging and discharging speed. Reasonable location and capacity can not only effectively smooth the volatility of wind and solar output, but also improve the system voltage quality, reduce network losses, and improve economy.

[0003] However, the wind and solar energy storage systems in the current low-carbon economic parks are generally centralized energy storage, and the internal batteries have frequent charging and discharging problems, resulting in a short battery life. In addition, centralized energy storage also leads to poor efficiency in optimizing the dispatch of peak loads and valley filling in the power system. Its comprehensive utilization effect is not good. Summary of the invention

[0004] The purpose of this application is: to solve the above-mentioned technical problems, this application provides a wind and solar energy storage optimization method and system for a low-carbon economic park, aiming to improve the operating efficiency of the energy storage system, increase the service life of the battery, and reduce the overall operation and maintenance costs.

[0005] In some embodiments of the present application, multiple energy storage sub-areas are established according to the park parameters, and corresponding energy storage modules are established for each energy storage sub-area, so as to perform regional regulation within the park, ensure the normal power supply demand within the park during the off-peak period of wind and solar power generation, improve the peak-shaving and valley-filling optimization scheduling efficiency of the power system, and reduce the overall operation and maintenance cost of the energy storage system.

[0006] In some embodiments of the present application, multiple energy storage modules are provided to reduce the charge and discharge frequency of a single battery, thereby increasing the service life of the battery. By establishing a collaborative model, each energy storage sub-area is jointly controlled to improve the ability of a single energy storage sub-area to cope with fluctuation risks and ensure the operation needs of users in the park. At the same time, through overall collaborative control, the overall operation and maintenance costs are reduced. Improve system voltage quality, reduce network losses, and enhance economic efficiency.

[0007] In some embodiments of the present application, a method for optimizing wind, solar and energy storage in a low-carbon economic park is provided, comprising:

[0008] Based on the park parameters, multiple energy storage sub-areas are established, and a series of energy storage sub-areas A is generated, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas;

[0009] Establish an energy storage coordination model and set the parameters of energy storage equipment in each energy storage sub-area;

[0010] The operating parameters of each energy storage sub-area are obtained according to the preset feedback time node, and it is determined whether to generate a correction instruction.

[0011] In some embodiments of the present application, the establishment of multiple energy storage sub-areas includes:

[0012] Establish a park evaluation model;

[0013] Obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model;

[0014]

[0015] Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park;

[0016] Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4);

[0017] If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1;

[0018] If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2;

[0019] If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

[0020] In some embodiments of the present application, the establishment of the energy storage coordination model includes:

[0021] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0022] Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model;

[0023] Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region;

[0024] Preset a first correlation evaluation value interval (F1, F2);

[0025] If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area;

[0026] Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region;

[0027] The energy storage coordination model is established based on all associated sub-tables.

[0028] In some embodiments of the present application, when setting the parameters of the energy storage devices in each energy storage sub-area, it includes:

[0029] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0030] Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area;

[0031] Generate energy storage module power range and capacity range of each energy storage sub-area in sequence;

[0032] Generate multiple first-level equipment plans;

[0033] Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans;

[0034] Set the i-th first-level equipment plan as the target first-level equipment plan;

[0035] Generate operational evaluation values ​​for target level 1 equipment plans;

[0036] Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan;

[0037] Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan;

[0038] The energy storage modules of each energy storage sub-area are set according to the secondary equipment plan.

[0039] In some embodiments of the present application, when generating the operation evaluation value of the target primary equipment plan, it includes:

[0040]

[0041] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

[0042] In some embodiments of the present application, determining whether to generate a correction instruction includes:

[0043] Establish multiple adjustment cycles;

[0044] Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle;

[0045] Generate joint power generation prediction curve;

[0046] Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve;

[0047] Generate control plans for each time interval based on preset objective functions and constraints;

[0048] Generate working parameters within the current adjustment cycle according to the entire control plan;

[0049] Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node;

[0050]

[0051] Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator;

[0052] If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

[0053] In some embodiments of the present application, a wind-solar-energy storage optimization system for a low-carbon economic park is provided, comprising:

[0054] The central control unit is used to establish multiple energy storage sub-areas according to the park parameters and generate an energy storage sub-area sequence A, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas;

[0055] An energy storage unit, comprising a plurality of energy storage modules, wherein the energy storage modules are arranged in the energy storage sub-area;

[0056] The central control unit comprises:

[0057] The first processing module establishes an energy storage synergy model;

[0058] A second processing module, used to set parameters of energy storage devices in each energy storage sub-area;

[0059] A first control module, used to obtain the operating parameters of each energy storage sub-area according to a preset feedback time node, and determine whether to generate a correction instruction;

[0060] The third processing module is used to establish a park evaluation model, obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model;

[0061]

[0062] Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park;

[0063] Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4);

[0064] If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1;

[0065] If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2;

[0066] If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

[0067] In some embodiments of the present application, the first processing module is further used to:

[0068] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0069] Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model;

[0070] Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region;

[0071] Preset a first correlation evaluation value interval (F1, F2);

[0072] If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area;

[0073] Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region;

[0074] The energy storage coordination model is established based on all associated sub-tables.

[0075] In some embodiments of the present application, the second processing module is used to:

[0076] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0077] Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area;

[0078] Generate energy storage module power range and capacity range of each energy storage sub-area in sequence;

[0079] Generate multiple first-level equipment plans;

[0080] Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans;

[0081] Set the i-th first-level equipment plan as the target first-level equipment plan;

[0082] Generate operational evaluation values ​​for target level 1 equipment plans;

[0083] Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan;

[0084] Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan;

[0085] Set the energy storage modules for each energy storage sub-area according to the secondary equipment plan;

[0086] Among them, when generating the operation evaluation value of the target first-level equipment plan, it includes:

[0087]

[0088] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

[0089] In some embodiments of the present application, the first control module is used to:

[0090] Establish multiple adjustment cycles;

[0091] Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle;

[0092] Generate joint power generation prediction curve;

[0093] Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve;

[0094] Generate control plans for each time interval based on preset objective functions and constraints;

[0095] Generate working parameters within the current adjustment cycle according to the entire control plan;

[0096] Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node;

[0097]

[0098] Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator;

[0099] If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

[0100] Compared with the prior art, the wind-solar energy storage optimization method and system for a low-carbon economic park in the embodiment of the present application has the following beneficial effects:

[0101] According to the park parameters, multiple energy storage sub-areas are established, and corresponding energy storage modules are established for each energy storage sub-area, so as to adjust the park in different regions, ensure the normal power supply demand in the park during the off-peak period of wind and solar power generation, improve the peak-shaving and valley-filling optimization scheduling efficiency of the power system, and reduce the overall operation and maintenance cost of the energy storage system.

[0102] By setting up multiple energy storage modules, the charge and discharge frequency of a single battery is reduced, thereby increasing the service life of the battery. By establishing a collaborative model, each energy storage sub-area is jointly controlled to improve the ability of a single energy storage sub-area to cope with fluctuation risks and ensure the operation needs of users in the park. At the same time, through overall collaborative control, the overall operation and maintenance costs are reduced. Improve system voltage quality, reduce network losses, and improve economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 It is a flow chart of a method for optimizing wind, solar and energy storage in a low-carbon economic park in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0104] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0105] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0106] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0107] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0108] like Figure 1 As shown, a wind-solar energy storage optimization method for a low-carbon economic park in a preferred embodiment of the present application includes:

[0109] S101: Establish multiple energy storage sub-areas based on park parameters, and generate an energy storage sub-area sequence A, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas;

[0110] S102: Establishing an energy storage coordination model and setting energy storage device parameters in each energy storage sub-area;

[0111] S103: Obtaining operating parameters of each energy storage sub-area according to a preset feedback time node, and determining whether to generate a correction instruction.

[0112] Specifically, when establishing multiple energy storage sub-areas, it includes:

[0113] Establish a park evaluation model;

[0114] Obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model;

[0115]

[0116] Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park;

[0117] Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4);

[0118] If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1;

[0119] If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2;

[0120] If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

[0121] Specifically, the park evaluation indicators include, but are not limited to, parameters such as wind turbine power generation fluctuation frequency, photovoltaic power generation fluctuation frequency, park area, user density within the park, user distribution within the park, and user electricity demand.

[0122] Specifically, the greater the park evaluation value, the higher the current operation complexity of the park. By dynamically adjusting the number of energy storage sub-areas, the scheduling efficiency of the energy storage modules in each energy storage sub-area is improved, the power grid operation quality and user needs in each energy storage sub-area are met, and the operation efficiency of the power system within the park is guaranteed.

[0123] Specifically, in the above embodiment, multiple energy storage sub-areas are established according to the park parameters, and corresponding energy storage modules are established for each energy storage sub-area, so as to perform regional regulation within the park, ensure the normal power supply demand within the park during the off-peak period of wind and solar power generation, improve the peak-shaving and valley-filling optimization scheduling efficiency of the power system, and reduce the overall operation and maintenance cost of the energy storage system.

[0124] In a preferred embodiment of the present application, when establishing an energy storage coordination model, it includes:

[0125] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0126] Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model;

[0127] Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region;

[0128] Preset a first correlation evaluation value interval (F1, F2);

[0129] If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area;

[0130] Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region;

[0131] The energy storage coordination model is established based on all associated sub-tables.

[0132] Specifically, based on parameters such as user types in each energy storage sub-area, grid demand, and power transmission paths between each other, the correlation evaluation values ​​between each energy storage sub-area are set.

[0133] Specifically, the higher the correlation evaluation value, the higher the similarity between the corresponding energy storage sub-areas, and the lower the mutual electricity call cost. The first-level associated sub-area means that when the power grid in the target energy storage sub-area fluctuates violently and causes unstable operation, the energy storage coordination model can be used to control the energy storage modules in each first-level associated sub-area for auxiliary adjustment, thereby ensuring the stability of the power grid operation within the park.

[0134] Specifically, in the above embodiment, by establishing a collaborative model, each energy storage sub-area is jointly controlled to improve the ability of a single energy storage sub-area to cope with fluctuation risks.

[0135] In a preferred embodiment of the present application, the target energy storage sub-regions are selected in sequence according to the energy storage sub-region sequence A;

[0136] Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area;

[0137] Generate energy storage module power range and capacity range of each energy storage sub-area in sequence;

[0138] Generate multiple first-level equipment plans;

[0139] Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans;

[0140] Set the i-th first-level equipment plan as the target first-level equipment plan;

[0141] Generate operational evaluation values ​​for target level 1 equipment plans;

[0142] Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan;

[0143] Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan;

[0144] The energy storage modules of each energy storage sub-area are set according to the secondary equipment plan.

[0145] Specifically, a single first-level equipment plan includes the energy storage capacity and energy storage power of the energy storage modules in each energy storage sub-area. By setting the unit energy storage capacity and unit energy storage power, multiple first-level equipment plans are constructed based on the principle of random combination.

[0146] Specifically, the energy storage capacity and energy storage power of each energy storage module in a single primary equipment plan are integer multiples of the unit energy storage capacity and the unit energy storage power.

[0147] Specifically, the best secondary equipment plan is selected based on the optimization principle. Under the premise of ensuring the peak shaving and valley filling optimization scheduling efficiency of the power system, the overall operation and maintenance cost of the energy storage system within the park is reduced and the economy is increased.

[0148] Specifically, when generating the operation evaluation value of the target first-level equipment plan, it includes:

[0149]

[0150] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

[0151] Specifically, the influence factor of the energy storage sub-area is set according to different levels of the energy storage sub-area. The level of the energy storage sub-area can be set according to the users in the energy storage sub-area. The higher the level, the greater the corresponding influence factor.

[0152] Specifically, auxiliary equipment includes capacity management modules, converters and other equipment, and operation and maintenance costs include fixed operation and maintenance costs and variable operation and maintenance costs. The more energy storage modules there are, the lower the variable operation and maintenance cost of a single energy storage module, the longer the service life, and the higher the recovery value.

[0153] Specifically, in the above embodiment, by establishing an optimization model, the equipment parameters of the energy storage modules in each energy storage sub-area are adjusted to the best, thereby reducing the overall operation and maintenance cost of the energy storage system in the park.

[0154] In a preferred embodiment of the present application, when determining whether to generate a correction instruction, the process includes:

[0155] Establish multiple adjustment cycles;

[0156] Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle;

[0157] Generate joint power generation prediction curve;

[0158] Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve;

[0159] Generate control plans for each time interval based on preset objective functions and constraints;

[0160] Generate working parameters within the current adjustment cycle according to the entire control plan;

[0161] Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node;

[0162]

[0163] Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator;

[0164] If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

[0165] Specifically, the objective function includes the annual cost function that takes into account the peak-to-valley difference in benefits, the system network loss cost function and the power grid system stability function. The constraints include system tidal constraints, branch current constraints, charging and discharging power constraints of each energy storage module, energy storage capacity constraints and energy storage capacity balance constraints, user demand constraints, etc.

[0166] Specifically, the control plan within a single time interval refers to the charge and discharge status, charging power or discharging power, charging amount or discharging amount, etc. of each energy storage module within the current time interval.

[0167] Specifically, the fluctuation evaluation indicators include but are not limited to light intensity, wind speed, user demand, photovoltaic power generation, wind turbine power generation and other parameters. The standard value of each fluctuation evaluation indicator is set according to the prediction model. The larger the fluctuation evaluation value, the more unstable the operation of the current power grid system in the park.

[0168] Specifically, according to the correction instructions, the operating parameters of each energy storage sub-area are obtained in turn. If the operating fluctuation of the power grid in a single energy storage sub-area is too large, the energy storage modules in the corresponding first-level associated sub-area are called in time for coordinated adjustment to ensure the stability of the overall operation.

[0169] Based on another preferred embodiment of a wind-solar-energy storage optimization method for a low-carbon economic park in any of the above preferred embodiments, this preferred embodiment provides a wind-solar-energy storage optimization system for a low-carbon economic park, including:

[0170] The central control unit is used to establish multiple energy storage sub-areas according to the park parameters and generate an energy storage sub-area sequence A, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas;

[0171] An energy storage unit, comprising a plurality of energy storage modules, wherein the energy storage modules are arranged in the energy storage sub-area;

[0172] The central control unit includes:

[0173] The first processing module establishes an energy storage synergy model;

[0174] A second processing module, used to set parameters of energy storage devices in each energy storage sub-area;

[0175] A first control module, used to obtain the operating parameters of each energy storage sub-area according to a preset feedback time node, and determine whether to generate a correction instruction;

[0176] The third processing module is used to establish a park evaluation model, obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model;

[0177]

[0178] Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park;

[0179] Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4);

[0180] If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1;

[0181] If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2;

[0182] If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

[0183] In a preferred embodiment of the present application, the first processing module is also used for:

[0184] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0185] Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model;

[0186] Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region;

[0187] Preset a first correlation evaluation value interval (F1, F2);

[0188] If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area;

[0189] Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region;

[0190] The energy storage coordination model is established based on all associated sub-tables.

[0191] In a preferred embodiment of the present application, the second processing module is used to:

[0192] Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A;

[0193] Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area;

[0194] Generate energy storage module power range and capacity range of each energy storage sub-area in sequence;

[0195] Generate multiple first-level equipment plans;

[0196] Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans;

[0197] Set the i-th first-level equipment plan as the target first-level equipment plan;

[0198] Generate operational evaluation values ​​for target level 1 equipment plans;

[0199] Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan;

[0200] Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan;

[0201] Set the energy storage modules for each energy storage sub-area according to the secondary equipment plan;

[0202] Among them, when generating the operation evaluation value of the target first-level equipment plan, it includes:

[0203]

[0204] Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

[0205] In a preferred embodiment of the present application, the first control module is used to:

[0206] Establish multiple adjustment cycles;

[0207] Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle;

[0208] Generate joint power generation prediction curve;

[0209] Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve;

[0210] Generate control plans for each time interval based on preset objective functions and constraints;

[0211] Generate working parameters within the current adjustment cycle according to the entire control plan;

[0212] Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node;

[0213]

[0214] Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator;

[0215] If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

[0216] According to the first concept of this application, multiple energy storage sub-areas are established according to the park parameters, and corresponding energy storage modules are established for each energy storage sub-area, so as to adjust the park in different regions, ensure the normal power supply demand in the park during the off-peak period of wind and solar power generation, improve the peak-shaving and valley-filling optimization scheduling efficiency of the power system, and reduce the overall operation and maintenance cost of the energy storage system.

[0217] According to the second concept of this application, by setting up multiple energy storage modules, the charge and discharge frequency of a single battery is reduced, thereby increasing the service life of the battery. By establishing a collaborative model, each energy storage sub-area is jointly controlled to improve the ability of a single energy storage sub-area to cope with fluctuation risks and ensure the operation needs of users in the park. At the same time, through overall collaborative control, the overall operation and maintenance costs are reduced. Improve system voltage quality, reduce network losses, and enhance economic efficiency.

[0218] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A wind and solar energy storage optimization method for a low-carbon economic park, It is characterized in that include: Based on the park parameters, multiple energy storage sub-areas are established, and a series of energy storage sub-areas A is generated, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas; Establish an energy storage coordination model and set the parameters of energy storage equipment in each energy storage sub-area; The operating parameters of each energy storage sub-area are obtained according to the preset feedback time node, and it is determined whether to generate a correction instruction.

2. The wind-solar-energy storage optimization method for a low-carbon economic park as claimed in claim 1, It is characterized in that The establishment of multiple energy storage sub-areas includes: Establish a park evaluation model; Obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model; Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park; Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4); If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1; If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2; If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

3. The wind and solar energy storage optimization method for a low-carbon economic park as claimed in claim 2, It is characterized in that The establishment of the energy storage coordination model includes: Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A; Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model; Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region; Preset a first correlation evaluation value interval (F1, F2); If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area; Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region; The energy storage coordination model is established based on all associated sub-tables.

4. The wind-solar-energy storage optimization method for a low-carbon economic park as claimed in claim 3, It is characterized in that When setting the parameters of the energy storage equipment in each energy storage sub-area, it includes: Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A; Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area; Generate energy storage module power range and capacity range of each energy storage sub-area in sequence; Generate multiple first-level equipment plans; Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans; Set the i-th first-level equipment plan as the target first-level equipment plan; Generate operational evaluation values ​​for target level 1 equipment plans; Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan; Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan; The energy storage modules of each energy storage sub-area are set according to the secondary equipment plan.

5. The wind-solar-energy storage optimization method for a low-carbon economic park as claimed in claim 4, It is characterized in that When generating the operational evaluation value of the target first-level equipment plan, include: Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

6. The wind-solar-energy storage optimization method for a low-carbon economic park as claimed in claim 5, It is characterized in that When judging whether to generate a correction instruction, it includes: Establish multiple adjustment cycles; Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle; Generate joint power generation prediction curve; Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve; Generate control plans for each time interval based on preset objective functions and constraints; Generate working parameters within the current adjustment cycle according to the entire control plan; Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node; Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator; If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

7. A wind-solar-energy storage optimization system for a low-carbon economic park, using the wind-solar-energy storage optimization method for a low-carbon economic park as described in any one of claims 1 to 6. It is characterized in that include: The central control unit is used to establish multiple energy storage sub-areas according to the park parameters and generate an energy storage sub-area sequence A, A = (a1, a2...an), where ai is the i-th energy storage sub-area; n is the number of energy storage sub-areas; An energy storage unit, comprising a plurality of energy storage modules, wherein the energy storage modules are arranged in the energy storage sub-area; The central control unit comprises: The first processing module establishes an energy storage synergy model; A second processing module, used to set parameters of energy storage devices in each energy storage sub-area; A first control module, used to obtain the operating parameters of each energy storage sub-area according to a preset feedback time node, and determine whether to generate a correction instruction; The third processing module is used to establish a park evaluation model, obtain park parameters, and generate a park evaluation value t according to the park parameters and the park evaluation model; Among them, ki is the reference value of the evaluation index of the i-th park; θ is the number of evaluation indicators of the park; αi is the influencing factor of the evaluation index of the i-th park; Preset the first park evaluation value interval (T1, T2), the second park evaluation value interval (T2, T3) and the third park evaluation value interval (T3, T4); If the park evaluation value t is within the preset first park evaluation value interval, the number n of the energy storage sub-areas is set to the preset first energy storage sub-area number n1, that is, n=n1; If the park evaluation value t is within the preset second park evaluation value interval, the number n of the energy storage sub-areas is set to the preset second energy storage sub-area number n2, that is, n=n2; If the park evaluation value t is within the preset third park evaluation value interval, the number n of the energy storage sub-areas is set to the preset third number n3 of the energy storage sub-areas, that is, n=n3; and n1<n2<n3.

8. The wind-solar-energy storage optimization system for a low-carbon economic park as claimed in claim 7, It is characterized in that The first processing module is also used for: Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A; Generate a correlation evaluation value of the target energy storage sub-area and each energy storage sub-area according to a preset correlation model; Establishing a correlation evaluation value sequence F, F = (f1, f2 ... fn), wherein fi is the correlation evaluation value between the target energy storage sub-region and the i-th energy storage sub-region; Preset a first correlation evaluation value interval (F1, F2); If fi is in the preset first associated evaluation value area, the i-th energy storage sub-area is set as the first-level associated sub-area of ​​the target energy storage sub-area; Generate a related sub-table of the target energy storage sub-region according to all first-level related sub-regions of the target energy storage sub-region; The energy storage coordination model is established based on all associated sub-tables.

9. The wind-solar-energy storage optimization system for a low-carbon economic park as claimed in claim 8, It is characterized in that The second processing module is used for: Select the target energy storage sub-areas in sequence according to the energy storage sub-area sequence A; Setting the energy storage module power range and capacity range of the target energy storage sub-area according to the user demand parameters of the target energy storage sub-area; Generate energy storage module power range and capacity range of each energy storage sub-area in sequence; Generate multiple first-level equipment plans; Establish a first-level equipment plan sequence B, B = (b1, b2...bm), where bi is the i-th first-level equipment plan; m is the number of first-level equipment plans; Set the i-th first-level equipment plan as the target first-level equipment plan; Generate operational evaluation values ​​for target level 1 equipment plans; Establish an operation evaluation value sequence C, C = (c1, c2...cm), where ci is the operation evaluation value of the i-th primary equipment plan; Set the first-level equipment plan corresponding to the maximum value cmax in the operation evaluation value sequence C as the second-level equipment plan; Set the energy storage modules for each energy storage sub-area according to the secondary equipment plan; Among them, when generating the operation evaluation value of the target first-level equipment plan, it includes: Among them, e1 is the preset first weight coefficient; e2 is the preset second weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; βi is the influencing factor of the i-th energy storage sub-area; di is the anti-fluctuation evaluation value of the i-th energy storage sub-area set based on the energy storage synergy model; η is the discount factor; Pi is the power of the energy storage module in the i-th energy storage sub-area; r1 is the unit power price of the energy storage module; Ui is the capacity of the energy storage module in the i-th energy storage sub-area; r2 is the unit capacity price of the energy storage module; J2 is the sum of the auxiliary equipment cost and operation and maintenance cost in the target first-level equipment plan.

10. The wind-solar-energy storage optimization system for a low-carbon economic park as claimed in claim 9, It is characterized in that The first control module is used for: Establish multiple adjustment cycles; Obtain wind turbine power prediction curve and photovoltaic power prediction curve of the current regulation cycle; Generate joint power generation prediction curve; Establish multiple time intervals within the current regulation cycle according to the combined power generation prediction curve; Generate control plans for each time interval based on preset objective functions and constraints; Generate working parameters within the current adjustment cycle according to the entire control plan; Generate a fluctuation evaluation value h of the current adjustment cycle according to the preset feedback time node; Among them, y is the number of fluctuation evaluation indicators; gi is the influencing factor of the ith fluctuation evaluation indicator; wi is the real-time reference value of the ith fluctuation evaluation indicator; w'i is the standard reference value of the ith fluctuation evaluation indicator; If h is greater than the preset first fluctuation evaluation value threshold H1, a correction instruction is generated.

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