Multi-Type Energy Storage Optimization Configuration Method and System Considering the Coordinated Support of Electric Power and Electric Quantity

Abstract

The present invention discloses a multi-type energy storage optimal configuration method and system considering coordinated power and energy support, which acquires the operation parameters of a new energy power station and a multi-type energy storage system; solves a pre-established capacity optimal configuration model of the multi-type energy storage system on the new energy side according to the operation parameters of the new energy power station and the multi-type energy storage system, obtains the rated capacity and rated power of the multi-type energy storage system, and preferentially selects the capacity optimal configuration scheme of the multi-type energy storage system on the new energy power station side. The present invention ensures the rationality and investment economy of configuring a multi-type energy storage system in a new energy power station, and ensures the safety and reliability of large-scale integration of new energy into the power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrical engineering, and particularly relates to a multi-type energy storage optimal configuration method and system considering the coordinated support of electric power and electricity volume. Background Art

[0002] Due to the volatility and intermittency of new energy power generation, in terms of consumption, the problem of abandoned electricity is particularly prominent; in terms of reliability, after new energy replaces traditional energy as the main energy source, the frequency characteristics and stability of the power grid system will inevitably be severely weakened. If high-proportion new energy is to develop stably, the situation of relying solely on single traditional energy regulation needs to be changed urgently. New energy itself should have the ability of active support and share the responsibilities and obligations of the safe and stable operation of the system with traditional energy.

[0003] According to the clear requirements of GB 38755-2019 "Power System Safety and Stability Guide", "New energy should have the ability of primary frequency modulation and fast voltage regulation, and provide necessary inertia for the power grid in areas with high proportion of new energy."

[0004] At present, the application requirements of new energy power stations for energy storage mainly include four application modes: inertia support, primary frequency modulation, compensation for power prediction error, and reduction of abandoned electricity rate. The technical requirements for energy storage in these four application modes are cross-coupled in time series. Considering that the charge-discharge cycle times of the battery energy storage system are relatively limited, how to use multi-type energy storage to enable the same set of energy storage system to take into account four application scenarios and achieve the efficient application of the energy storage system, while achieving the economic and technical goals of energy storage capacity investment is an urgent problem to be solved.

[0005] Existing research focuses on the optimal configuration method of energy storage systems in new energy power stations with a single application mode or a combined application mode of two of them, such as compensating for power prediction error, reducing abandoned electricity rate, improving the inertia support and primary frequency modulation ability of new energy power stations. There is still no relatively mature and systematic in-depth research result on the optimal configuration of energy storage capacity that takes into account four application modes of compensating for power prediction error, reducing abandoned electricity rate, inertia support, and primary frequency modulation in new energy power stations. Summary of the Invention

[0006] The purpose of the present invention is to realize that the energy storage system configured in a new energy power station takes into account four application modes: inertia support, primary frequency modulation, compensation for power prediction error, and reduction of abandoned electricity rate. A multi-type energy storage optimal configuration method and system considering the coordinated support of electric power and electricity volume are provided to solve the defects existing in the prior art. The present invention ensures the rationality and investment economy of configuring a multi-type energy storage system in a new energy power station, and ensures the safety and reliability of large-scale integration of new energy into the power grid.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] A multi-type energy storage optimization configuration method considering coordinated power and energy support, including:

[0009] Obtain the operation parameters of the new energy power station and the multi-type energy storage system;

[0010] Solve the pre-established capacity optimization configuration model of the multi-type energy storage system on the new energy side according to the operation parameters of the new energy power station and the multi-type energy storage system, obtain the rated capacity and rated power of the multi-type energy storage system, and select the capacity optimization configuration scheme of the multi-type energy storage system on the new energy power station side with the maximum annual on-grid electricity of the new energy power station and the maximum annual net income of the multi-type energy storage system during the planning period of the new energy power station as the comprehensive goal.

[0011] Further, the multi-type energy storage system includes a battery energy storage system and a power-type energy storage system.

[0012] Further, the operation parameters of the new energy power station and the multi-type energy storage system include the output values, predicted values, cost coefficients, replacement times of each component in the new energy power station and the multi-type energy storage system, and the operation life of the new energy power station.

[0013] Further, the capacity optimization configuration model of the multi-type energy storage system on the new energy side consists of an objective function and constraint conditions;

[0014] The objective function includes the maximum annual on-grid electricity of the new energy power station and the maximum annual net income of the multi-type energy storage system during the planning period of the new energy power station;

[0015] The constraint conditions include the energy storage state of charge constraint, the minimum energy storage configuration constraint, the power constraint of the multi-type energy storage system, the curtailment rate constraint, and the total charge and discharge power balance constraint of the multi-type energy storage system with the battery energy storage system and the power-type energy storage system.

[0016] Further, the objective function is expressed as follows:

[0017] F = max{f1, f2}

[0018] Wherein, F is the objective function; f1 is the annual on-grid electricity of the new energy power station; f2 is the annual net income of the multi-type energy storage system during the planning period of the new energy power station;

[0019] The annual on-grid electricity of the new energy power station is expressed as follows:

[0020]

[0021] Wherein, f1 is the annual on-grid electricity of the new energy power station; is the actual output power of the new energy power station at time t; is the output power of the battery energy storage system at time t; is the output power of the power energy storage system at time t; t is the current time; T is the total number of time periods in a year;

[0022] The annual net income of multiple types of energy storage systems during the planning period of the new energy power station is expressed as follows:

[0023] f2 = C on + C gap + C rel - C LCC

[0024] Where f2 is the annual net income of multiple types of energy storage systems; C on is the income obtained by increasing the annual electricity fed into the grid; C gap is the income reduction of the assessment by compensating for the power prediction error; C rel is the income obtained by exempting the active power reserve and increasing the annual electricity fed into the grid; C LCC is the annual value of the cost of multiple types of energy storage systems during the planning period.

[0025] Furthermore, the income obtained by increasing the annual electricity fed into the grid is expressed as follows:

[0026]

[0027] Where N is the total service life of multiple types of energy storage systems; n is the number of years of use; C eon is the on-grid electricity price of the power station during time t; E ESS_disch is the total discharge amount of multiple types of energy storage systems at time t; T is the total number of time periods in a year; r is the discount rate;

[0028] The income reduction of the assessment by compensating for the power prediction error is expressed as follows:

[0029]

[0030]

[0031] Where Acc N is the assessment value of the day-ahead prediction accuracy; Acc is the day-ahead prediction accuracy; Cap is the maximum installed capacity of the new energy power station on the assessment day; is the actual power of the new energy power station during time t; is the predicted power of the new energy power station during time t; a is the number of prediction points for daily assessment;

[0032] The income obtained by exempting the active power reserve and increasing the annual electricity fed into the grid is expressed as follows:

[0033]

[0034] Where is the installed electricity capacity of the new energy power station;

[0035] The annual value of the cost of the multi-type energy storage system within the planned year is expressed as follows:

[0036] C LCC = C inv + C om + C sec + C rep + C rec

[0037] In the formula, C inv is the initial annual construction cost; C om is the annual operation and maintenance cost; C sec is the annual auxiliary equipment cost; C rep is the annual equipment replacement cost; C rec is the annual equipment scrap salvage recovery cost.

[0038] Furthermore, the initial annual construction cost is expressed as follows:

[0039]

[0040] In the formula, k is the number of equipment replacements of the battery energy storage system; is the unit power investment cost of the battery energy storage system; is the unit power investment cost of the power-type energy storage system; is the unit capacity investment cost of the battery energy storage system; is the unit capacity investment cost of the power-type energy storage system; is the rated power of the battery energy storage system; is the rated power of the power-type energy storage system; is the rated capacity of the power-type energy storage system; is the rated capacity of the battery energy storage system; r is the discount rate;

[0041] The annual operation and maintenance cost is expressed as follows:

[0042]

[0043] In the formula, is the operation and maintenance cost per unit charge / discharge of the multi-type energy storage at time t; is the charge / discharge amount of the multi-type energy storage at time t;

[0044] The annual auxiliary equipment cost is expressed as follows:

[0045]

[0046]

[0047] In the formula, is the unit power auxiliary cost of the battery energy storage system; is the unit power auxiliary cost of the power-type energy storage system;

[0048] The annual equipment replacement cost is expressed as follows:

[0049]

[0050] In the formula, is the unit capacity investment cost of the battery energy storage system; is the rated capacity of the power-type energy storage system; α is the average annual decline ratio of the energy storage system cost;

[0051] The annual equipment scrap salvage recovery cost is expressed as follows:

[0052]

[0053] In the formula, δ is the proportion of the recovered part in the battery energy storage system; γ is the equipment scrap salvage recovery cost coefficient; β is the βth replacement of part of the battery energy storage.

[0054] Furthermore, the energy storage state of charge constraint is expressed as follows:

[0055]

[0056]

[0057]

[0058]

[0059] In the formula, are the initial states of charge of the battery energy storage system and the power-type energy storage system respectively; are the states of charge of the battery energy storage system and the power-type energy storage system at time t respectively; are the output powers of the battery energy storage system and the power-type energy storage system at time t respectively; are the rated capacities of the battery energy storage system and the power-type energy storage system respectively; are the minimum and maximum states of charge of the battery energy storage system;

[0060] The minimum energy storage configuration constraint is expressed as follows:

[0061]

[0062]

[0063]

[0064] In the formula, is the total power and total capacity requirements of the multi-type energy storage system for the inertia support mode and the primary frequency regulation mode at time t; is the output power and output power of the battery energy storage system at time t; is the output power and output power of the power-type energy storage system at time t; is the inertia support output power; is the primary frequency regulation output power; ξ k is the control coefficient of the inertia support mode and the primary frequency regulation mode; SOC is the SOC value of the multi-type energy storage system;

[0065] The power constraint of the multi-type energy storage system is expressed as follows:

[0066]

[0067]

[0068] In the formula, are the output power and rated power of the battery energy storage system at the current moment, respectively; are the output power and rated power of the power-type energy storage system at the current moment, respectively;

[0069] The curtailment rate constraint is expressed as follows:

[0070]

[0071] In the formula, is the loss power when curtailment occurs in the new energy power station throughout the year; is the output power of the new energy power station throughout the year; t is the time when curtailment occurs within a year;

[0072] The total charge-discharge power balance constraint of the multi-type energy storage system, the battery energy storage system, and the power-type energy storage system is expressed as follows:

[0073] P ESS_ch = P bess_ch + P pow_ch

[0074] P ESS_disch = P bess_disch + P pow_disch

[0075] In the formula, P ESS_ch 、P bess_ch 、P pow_ch are the charging powers of the multi-type energy storage system, the battery energy storage system, and the power-type energy storage system, respectively; P ESS_disch 、P bess_disch 、P pow_disch are the discharge powers of the multi-type energy storage system, the battery energy storage system, and the power-type energy storage system, respectively.

[0076] Further, the solution of the pre-established capacity optimization configuration model for multi-type energy storage systems on the new energy side is specifically as follows:

[0077] The particle swarm optimization algorithm is used to solve the pre-established capacity optimization configuration model for multi-type energy storage systems on the new energy side, including:

[0078] Randomly generate a capacity optimization configuration plan for the energy storage system on the new energy side, specifically initialize the velocity and position parameters of the particles;

[0079] Select the objective function and constraint conditions and update the velocity and position parameters of the particles;

[0080] Continuously iterate the velocity and position parameters of the particles to obtain the individual optimal solution and the global optimal solution, and finally obtain the optimal solution for the capacity optimization configuration of the multi-type energy storage system.

[0081] A multi-type energy storage capacity optimization configuration system considering source-storage collaborative support includes:

[0082] An operating parameter acquisition module: used to acquire the operating parameters of the new energy power station and the multi-type energy storage system;

[0083] An optimization configuration module: used to solve the pre-established capacity optimization configuration model for multi-type energy storage systems on the new energy side according to the operating parameters of the new energy power station and the multi-type energy storage system, obtain the rated capacity and rated power of the multi-type energy storage system, and select the capacity optimization configuration plan for the multi-type energy storage system on the new energy power station side with the maximum annual on-grid electricity of the new energy power station and the maximum annual net income of the multi-type energy storage system during the planning period of the new energy power station as the comprehensive goal.

[0084] Further, the multi-type energy storage system includes a battery energy storage system and a power-type energy storage system;

[0085] The operating parameters of the new energy power station and the multi-type energy storage system include the output values, predicted values, cost coefficients, replacement times of each component in the new energy power station and the multi-type energy storage system, and the operating life of the new energy power station.

[0086] Further, the capacity optimization configuration model for multi-type energy storage systems on the new energy side consists of an objective function and constraint conditions;

[0087] The objective function includes the maximum annual on-grid electricity of the new energy power station and the maximum annual net income of the multi-type energy storage system during the planning period of the new energy power station;

[0088] The constraint conditions include the energy storage state of charge constraint, the minimum configuration constraint of energy storage, the power constraint of multi-type energy storage systems, the curtailment rate constraint, and the total charge-discharge power balance constraint of multi-type energy storage systems, battery energy storage systems, and power-type energy storage systems.

[0089] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the multi-type energy storage optimization configuration method considering the coordinated support of electric power and electricity quantity.

[0090] Compared with the prior art, the present invention has the following beneficial technical effects:

[0091] The present invention is applicable to the optimization configuration of multi-type energy storage systems considering the coordinated support of electric power and electricity quantity in new energy power stations. In the capacity optimization configuration model of multi-type energy storage systems on the new energy side, through the combined power generation of the new energy power generation system and multi-type energy storage systems, the energy flow of the power station is adjusted in real time to achieve the goal of supporting the power grid considering the coordinated support of electric power and electricity quantity in new energy power stations, ensuring the rationality and investment economy of configuring multi-type energy storage systems in new energy power stations, and ensuring the safety and reliability of large-scale integration of new energy into the power grid.

[0092] Furthermore, in the optimization configuration solution, first, the operation parameters of the new energy power station and the energy storage system are input. Secondly, a capacity optimization configuration model of multi-type energy storage systems on the new energy side is established. Then, a capacity optimization configuration scheme of the energy storage system on the new energy side is randomly generated. Then, the objective function and constraint conditions are selected and the velocity and position parameters of the particles are updated. The particle parameters are continuously iterated to obtain the individual optimal solution and the global optimal solution. Finally, the optimal solution of the capacity optimization configuration of multi-type energy storage systems is obtained. For the purpose of large-scale grid connection of new energy power stations and meeting the requirements of considering the coordinated support of electric power and electricity quantity in new energy power stations, the capacity configuration of multi-type energy storage systems is reasonably calculated through the above method, so as to meet the four application modes of inertia support, primary frequency modulation, compensation for power prediction error, and reduction of curtailment rate. It not only satisfies the dual game of economic and technical objectives, but also solves the problem that the grid frequency fluctuation increases after connecting to the new energy power station, which weakens the reliability of the power grid. At the same time, it takes into account the capacity configuration problems in different application scenarios and economic development levels. Description of the Drawings

[0093] The accompanying drawings in the specification are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention.

[0094] Figure 1 Topological structure diagram for configuring multi-type energy storage systems for a new energy power station;

[0095] Figure 2 Solution diagram of the capacity optimization configuration model for configuring multi-type energy storage systems for a new energy power station;

[0096] Figure 3 Flow chart of an optimization configuration method for configuring multiple types of energy storage systems in a new energy power station;

[0097] Figure 4 Structure diagram of an optimization configuration system for configuring multiple types of energy storage systems in a new energy power station. Detailed implementation manners

[0098] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0099] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0100] An optimization configuration method for multiple types of energy storage considering coordinated power and energy support, as Figure 3 shown, configure multiple types of energy storage systems on the new energy power station side; obtain the operation parameters of the new energy power station and the multiple types of energy storage systems; solve the pre-established capacity optimization configuration model of the multiple types of energy storage systems on the new energy side according to the operation parameters of the new energy power station and the multiple types of energy storage systems to obtain the rated capacity and rated power of the multiple types of energy storage systems, and select the capacity optimization configuration scheme of the multiple types of energy storage systems on the new energy power station side with the maximum annual on-grid electricity of the new energy power station and the maximum annual net income of the multiple types of energy storage systems during the planning period of the new energy power station as the comprehensive goal.

[0101] This invention takes a new energy power station as the research object, aims to consider the coordinated support of power and electricity in the new energy power station and maximize the investment economy and technicality of the energy storage system capacity configuration, establishes an optimal capacity configuration model for multi-type energy storage systems on the new energy side, uses the particle swarm algorithm to solve the established optimal capacity configuration model for multi-type energy storage systems on the new energy side, obtains the rated capacity and rated power of the multi-type energy storage systems, and preferentially selects the optimal capacity configuration scheme for multi-type energy storage systems on the new energy side.

[0102] For the purpose of considering the coordinated support of power and electricity in the new energy power station to the power grid and meeting the requirement of configuring multi-type energy storage systems in the new energy power station, the main circuit structure and power flow of the multi-type energy storage systems configured in the new energy power station are as Figure 1 shown, which consists of physical power devices such as a photovoltaic power generation system, a battery energy storage system, and a power-type energy storage system, as well as the energy management system of the new energy power station (in the figure is the output power of the photovoltaic power generation system, are the active powers output by the battery energy storage system and the power-type energy storage system respectively). This system can use various power electronic controllers and control strategies to achieve the purpose of using the charging and discharging states of the multi-type energy storage systems to control and realize the coordinated support of power and electricity to the power grid. The energy management system of the new energy power station mainly collects and detects in real time the active powers output by the new energy power generation system and the multi-type energy storage systems, the charging and discharging states of each component of the multi-type energy storage systems, and the system regulation information such as the real-time frequency of the power grid, and combines with the energy management system of the new energy power station to implement the coordinated control of the new energy power station and the multi-type energy storage systems, and conduct the optimal management of the energy.

[0103] As Figure 2 shown, the specific process of solving the optimal capacity configuration model of the multi-type energy storage systems configured in the new energy power station is as follows:

[0104] Step 1: Input the operation parameters of the new energy power station and the multi-type energy storage systems, including the output values and predicted values of each component of the new energy power station and the multi-type energy storage systems, the operation life of the new energy power station, the cost coefficients and replacement times of each component, etc.;

[0105] Step 2: Establish an optimal capacity configuration model for multi-type energy storage systems on the new energy side;

[0106] Step 3: Randomly generate an optimal capacity configuration scheme for the energy storage system on the new energy side, that is, initialize the particle swarm parameters and randomly generate the rated power and rated capacity parameters of the first-generation multi-type energy storage systems;

[0107] Step 4: Select the objective function and the corresponding constraint conditions as needed;

[0108] Step 5: Calculate the adaptive particle inertia weight, and thus calculate the particle velocity and position parameters;

[0109] Step 6: Calculate the fitness of the objective function through particle parameters;

[0110] Step 7: Compare the calculated function fitness and update the individual optimal value and the global optimal value;

[0111] Step 8: Update the capacity optimization configuration plan of the new energy side energy storage system, that is, update the rated power and capacity of multiple types of energy storage systems, that is, calculate and update the particle velocity and position parameters;

[0112] Step 9: Determine whether the termination condition is reached. If so, enter Step 9; if not, return to Step 6;

[0113] Step 10: Output the optimal solution of the capacity optimization of multiple types of energy storage systems.

[0114] Among them, the capacity optimization model of multiple types of energy storage systems on the new energy power station side consists of an objective function and constraint conditions, as follows:

[0115] I. Objective function

[0116] 1. Maximum double-objective function for capacity optimization of multiple types of energy storage systems on the new energy power station side

[0117] F = max{f1, f2} (1)

[0118] In the formula, f1 is the annual electricity output of the new energy power station to the grid; f2 is the annual net income of multiple types of energy storage systems;

[0119] 2. Annual electricity output of the new energy power station to the grid

[0120] The maximum value of the annual electricity output of the new energy power station to the grid is the sum of the algebraic differences between the electricity actually generated by the power station and the electricity output of the energy storage system within one year. Its calculation formula is as follows:

[0121]

[0122] In the formula, is the actual output power of the new energy power station at time t; is the output power of the battery energy storage system at time t; is the output power of the power-type energy storage system at time t; t is the current time; T is the total number of time periods per year;

[0123] 3. A multiple-type energy storage system composed of a battery energy storage system and a power-type energy storage system. Considering the life attenuation process of the battery energy storage system, the annual net income of the multiple-type energy storage system within the 25-year planning period of the new energy power station is taken as the optimization goal:

[0124] f2 = C on + C gap + C rel-C LCC (3)

[0125] In the formula, C on is the revenue obtained by increasing the annual grid-connected power; C gap is the revenue reduction of the assessment for compensating the power prediction error; C rel is the revenue obtained by exempting the active power reserve and increasing the annual grid-connected power; C LCC is the annual value of the cost of the multi-type energy storage system within the planning year.

[0126] (1) Revenue that can be obtained by a new energy power station after configuring a multi-type energy storage system

[0127] 1) Revenue obtained by increasing the annual grid-connected power

[0128] Partially or fully store the curtailed power of the new energy power station during the restricted power generation period in the battery energy storage system, and then during the non-limited power period, based on the SOC callback strategy, compensate for the power prediction error of the power grid to obtain the revenue of increasing the annual grid-connected power:

[0129]

[0130] In the formula, N is the total service life of the multi-type energy storage system; n is the number of years of use; C eon is the on-grid electricity price of the power station's power generation at time t; E ESS_disch is the total discharge amount of the multi-type energy storage system at the t-th moment; T is the total number of moments per year; r is the discount rate;

[0131] 2) Revenue reduction of the assessment for compensating the power prediction error

[0132] The revenue brought by compensating the power prediction error of the new energy power station refers to the reduction of the annual prediction deviation assessment cost of the new energy power station by configuring a multi-type energy storage system. When the accuracy rate is lower than the daily-ahead prediction accuracy rate assessment value Acc N an assessment cost is generated. Since the daily average prediction error accuracy rate of the new energy power station reaches 95% after configuring a multi-type energy storage system and there is no assessment cost, the increased revenue for compensating the power prediction error annually is:

[0133]

[0134]

[0135] In the formula, Acc N is the daily-ahead prediction accuracy rate assessment value, which is taken as 85% in this embodiment; Acc is the daily-ahead prediction accuracy rate; Cap is the maximum starting capacity of the new energy power station on the assessment day; is the actual power of the new energy power station in the t-th period; is the predicted power of the new energy power station in the t-th period; a is the number of prediction points for the assessment on that day.

[0136] 3) Exempt active reserve and increase the annual electricity generation for revenue

[0137] Active reserve refers to the real-time reservation of a certain proportion of reserve active power to ensure power quality and the safe and stable operation of the system. Since it is more economical to configure energy storage in terms of cost than to retain active reserve, the active reserve is exempted to increase the annual electricity generation for revenue:

[0138]

[0139] In the formula, is the installed electricity of the new energy power station;

[0140] (2) Taking 25 years as the planning period and considering that equipment replacement is required for multi-type energy storage systems within their service life, the replacement times of the battery energy storage system are set as variables, and the power-type energy storage system does not need replacement. By superimposing the investment costs of multi-type energy storage systems, the annual equivalent cost of multi-type energy storage systems is obtained, and its calculation formula is:

[0141] The annual equivalent cost C of multi-type energy storage systems within the planning year LCC is

[0142] C LCC = C inv + C om + C sec + C rep + C rec (8)

[0143] In the formula, C inv is the initial annual construction cost; C om is the annual operation and maintenance cost; C sec is the annual auxiliary equipment cost; C rep is the annual equipment replacement cost; C rec is the annual equipment scrap residual value recovery cost;

[0144] 1) Initial annual construction cost

[0145] The initial annual construction cost is mainly the purchase of energy storage system equipment, etc., which is jointly determined by the respective powers and capacities of the battery energy storage system and the power-type energy storage system in the multi-type energy storage system.

[0146]

[0147] In the formula, k is the equipment replacement times of the battery energy storage system; is the unit power investment cost of the battery energy storage system; is the unit power investment cost of the power-type energy storage system; is the unit capacity investment cost of the battery energy storage system; is the investment cost per unit capacity of the power-type energy storage system; is the rated power of the battery energy storage system; is the rated power of the power-type energy storage system; is the rated capacity of the power-type energy storage system; is the rated capacity of the battery energy storage system; r is the discount rate, and the discount rate generally adopted in China's power planning is 8%.

[0148] 2) Annual operation and maintenance cost

[0149] It includes a series of hardware losses such as equipment commissioning, installation, and equipment loss during the planning year of the multi-type energy storage system.

[0150]

[0151] In the formula, is the operation and maintenance cost per unit charge / discharge of the multi-type energy storage at time t; is the charge / discharge amount of the multi-type energy storage at time t.

[0152] 3) Annual auxiliary equipment cost

[0153] In the multi-type energy storage system, in addition to the power-type energy storage system and the battery energy storage system, the costs of other auxiliary facilities such as software upgrades and maintenance of the energy management system (EM S ) etc. need to be considered, then the auxiliary equipment cost:

[0154]

[0155] In the formula, is the auxiliary cost per unit power of the battery energy storage system; is the auxiliary cost per unit power of the power-type energy storage system;

[0156] Then the annual auxiliary equipment cost is:

[0157]

[0158] 4) Annual equipment replacement cost

[0159] In the 25-year planning period, when the use efficiency of the battery energy storage system in the new energy power station energy storage system drops significantly and it can no longer be used, the system needs to be replaced with new equipment, and the replacement cost of the multi-type energy storage system is:

[0160]

[0161] In the formula, is the investment cost per unit capacity of the battery energy storage system; is the rated capacity of the power-type energy storage system; α is the average annual decline rate of the energy storage system cost.

[0162] 5) Annual equipment scrap residual value recovery cost

[0163] During the operation of multi-type energy storage systems every year, there are some equipment that are damaged or even scrapped due to improper maintenance or equipment aging. All of them need to be included in the recovery cost within the planning period of the multi-type energy storage system. Then the annual equipment scrap residual value recovery cost is:

[0164]

[0165] In the formula, δ is the proportion of the recovered part in the battery energy storage system; γ is the equipment scrap residual value recovery cost coefficient; β is the βth replacement of part of the battery energy storage.

[0166] II. Constraint conditions

[0167] (1) Requirements for the state of charge (SOC) of the energy storage

[0168] To avoid overcharging or over-discharging of the energy storage system and extend its service life, the allowable range of SOC is set as:

[0169]

[0170]

[0171]

[0172]

[0173] In the formula, are the initial states of charge of the battery energy storage system and the power-type energy storage system respectively; are the states of charge of the battery energy storage system and the power-type energy storage system at time t respectively; are the output powers of the battery energy storage system and the power-type energy storage system at time t respectively; are the rated capacities of the battery energy storage system and the power-type energy storage system respectively; is the minimum and maximum state of charge of the battery energy storage system, Δt is the sampling time difference, is the minimum and maximum state of charge of the power-type energy storage system. This parameter is to avoid overcharging and over-discharging of the battery energy storage system. Generally, can be taken as 10%, can be taken as 90%.

[0174] (2) Minimum energy storage configuration constraint

[0175] In the inertia support and primary frequency regulation mode, in order to effectively meet the energy storage requirements of this mode, the total power and total capacity of the multi-type energy storage system shall not be less than the power and capacity requirements of this mode, and it shall meet the condition that when the combined output of new energy energy storage drops to 10% of the installed capacity of the new energy power station, no further downward regulation is required:

[0176]

[0177]

[0178]

[0179] is the total power and total capacity requirements of the multi-type energy storage in Mode 1 "inertia support + primary frequency regulation mode" at time t; is the output power and output power quantity of the battery energy storage system at time t; is the output power and output power quantity of the power-type energy storage system at time t; is the inertia support output power; is the primary frequency regulation output power; ξ k is the control coefficient of Mode 1 "inertia support + primary frequency regulation mode"; SOC is the SOC value of the multi-type energy storage system;

[0180] (3) Power constraint of multi-type energy storage system

[0181] In order to extend the service life of the multi-type energy storage system and avoid overcharging and over-discharging phenomena, energy management constraints are introduced as follows:

[0182]

[0183]

[0184] In the formula, are respectively the current power and rated power of the battery energy storage system; are respectively the current power and rated power of the power-type energy storage system.

[0185] (4) Curtailment rate constraint

[0186] When the total output power of the new energy power station is greater than the limit value required by the grid dispatching, and the multi-type energy storage system cannot absorb the excess power, curtailment will occur at the power station. Dividing the total curtailment power of the new energy power station in 8760 hours throughout the year by the total power generation, the annual curtailment rate of the new energy power station after configuring the energy storage system can be obtained (the value does not exceed the limit value of 5%), and its curtailment rate calculation formula is

[0187]

[0188] In the formula, It is the loss power when power curtailment occurs in the new energy power station within 8760 hours of the whole year; It is the output power of the new energy power station within 8760 hours of the whole year; t is the number of hours of power curtailment phenomenon occurring within one year;

[0189] (5) The total charge-discharge power balance of multi-type energy storage systems, battery and power-type energy storage systems

[0190] P ESS_ch =P bess_ch +P pow_ch (25)

[0191] P ESS_disch =P bess_disch +P pow_disch (26)

[0192] In the formula, P ESS_ch , P bess_ch , P pow_ch are the charging powers of the multi-type energy storage system, battery energy storage system, and power-type energy storage system respectively; P ESS_disch , P bess_disch , P pow_disch are the discharging powers of the multi-type energy storage system, battery energy storage system, and power-type energy storage system respectively.

[0193] The present invention also discloses a multi-type energy storage capacity optimization configuration system considering source-storage collaborative support, as Figure 4 shown, including:

[0194] Configuration module: used to configure a multi-type energy storage system on the new energy power station side;

[0195] Operation parameter acquisition module: used to acquire the operation parameters of the new energy power station and the multi-type energy storage system;

[0196] Optimization configuration module: used to solve the pre-established capacity optimization configuration model of the multi-type energy storage system on the new energy side according to the operation parameters of the new energy power station and the multi-type energy storage system, obtain the rated capacity and rated power of the multi-type energy storage system, and preferentially select the capacity optimization configuration scheme of the multi-type energy storage system on the new energy power station side.

[0197] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0198] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0199] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0200] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0201] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the scope of its protection. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: after reading the present invention, those skilled in the art can still make various changes, modifications, or equivalent replacements to the specific implementation manners of the invention, but these changes, modifications, or equivalent replacements are all within the scope of the protection of the pending claims of the invention.

Claims

1. A multi-type energy storage optimization configuration method considering coordinated support of electric power and electricity quantity, characterized in that Including: Obtaining the operating parameters of a new energy power station and multiple types of energy storage systems; wherein, the multiple types of energy storage systems are configured on the side of the new energy power station, and the multiple types of energy storage systems include a battery energy storage system and a power-type energy storage system; Solving the pre-established capacity optimization configuration model of the multiple types of energy storage systems on the new energy side according to the operating parameters of the new energy power station and the multiple types of energy storage systems, obtaining the rated capacity and rated power of the multiple types of energy storage systems, and selecting the capacity optimization configuration scheme of the multiple types of energy storage systems on the new energy side with the maximum annual new energy power station grid-connected electricity and the maximum annual net income of the multiple types of energy storage systems within the planning period of the new energy power station as the comprehensive goal; The capacity optimization configuration model of the multiple types of energy storage systems on the new energy side consists of an objective function and constraint conditions; The objective function includes the maximum annual new energy power station grid-connected electricity and the maximum annual net income of the multiple types of energy storage systems within the planning period of the new energy power station; The constraint conditions include energy storage state of charge constraint, minimum energy storage configuration constraint, power constraint of multiple types of energy storage systems, curtailment rate constraint, and total charge-discharge power balance constraint of the multiple types of energy storage systems with the battery energy storage system and the power-type energy storage system; The objective function is expressed as follows: F = max{f1, f2} In the formula, F is the objective function; f1 is the annual new energy power station grid-connected electricity; f2 is the annual net income of the multiple types of energy storage systems within the planning period of the new energy power station; The annual new energy power station grid-connected electricity is expressed as follows: In the formula, f1 is the annual grid-connected power of the new energy power station; is the actual output power of the new energy power station at time t; is the output power of the battery energy storage system at time t; is the output power of the power-type energy storage system at time t; t is the current time; T is the total number of time periods per year; The annual net income of the multiple types of energy storage systems within the planning period of the new energy power station is expressed as follows: f2 = C on + C gap + C rel - C LCC Where, f2 is the annual net income of the multi-type energy storage system; C on is the income obtained by increasing the annual grid-connected power; C gap is the income reduction of the assessment for compensating the power prediction error; C rel is the income obtained by exempting the active reserve and increasing the annual grid-connected power; C LCC is the annual value of the cost of the multi-type energy storage system within the planning year; The income obtained by increasing the annual grid-connected electricity is expressed as follows: Wherein, N is the total service life of the multi-type energy storage system; n is the number of years of use; C eon is the on-grid electricity price of the power station's power generation at time t; E ESS_disch is the total discharge amount of the multi-type energy storage system at the t-th moment; T is the total number of moments per year; r is the discount rate; The income obtained by compensating for the reduction of the power prediction error assessment is expressed as follows: Where Acc N is the assessment value of the day-ahead prediction accuracy; Acc is the day-ahead prediction accuracy; Cap is the maximum operating capacity of the new energy power station on the assessment day; is the actual power of the new energy power station at time t; is the predicted power of the new energy power station at time t; a is the number of prediction points for daily assessment; The income obtained by exempting the active power reserve and increasing the annual grid-connected electricity is expressed as follows: In the formula, is the installed power generation of the new energy power station; The annual value of the cost of the multiple types of energy storage systems within the planning year is expressed as follows: C LCC = C inv + C om + C sec + C rep + C rec Where, C inv is the initial annual construction cost; C om is the annual operation and maintenance cost; C sec is the annual auxiliary equipment cost; C rep is the annual equipment replacement cost; C rec is the annual cost of recovering the salvage value of scrapped equipment.

2. The multi-type energy storage optimal configuration method considering the coordinated support of electric power and electricity quantity according to claim 1, characterized in that The operating parameters of the new energy power station and the multiple types of energy storage systems include the output values, predicted values, cost coefficients, replacement times of each component in the new energy power station and the multiple types of energy storage systems, and the operating years of the new energy power station.

3. The multi-type energy storage optimal configuration method considering the coordinated support of electric power and electricity quantity according to claim 1, characterized in that The initial annual construction cost is expressed as follows: Where k is the number of replacements of the battery energy storage system equipment; is the unit power investment cost of the battery energy storage system; is the unit power investment cost of the power-type energy storage system; is the unit capacity investment cost of the battery energy storage system; is the unit capacity investment cost of the power-type energy storage system; is the rated power of the battery energy storage system; is the rated power of the power-type energy storage system; is the rated capacity of the power-type energy storage system; is the rated capacity of the battery energy storage system; r is the discount rate; The annual operation and maintenance cost is expressed as follows: In the formula, is the operation and maintenance cost of the charging / discharging amount per unit of multi-type energy storage at time t; is the charging / discharging amount of multi-type energy storage at time t; The annual auxiliary equipment cost is expressed as follows: Wherein, is the unit power auxiliary cost of the battery energy storage system; is the unit power auxiliary cost of the power-type energy storage system; The annual equipment replacement cost is expressed as follows: In the formula, is the investment cost per unit capacity of the battery energy storage system; is the rated capacity of the power-type energy storage system; α is the average annual decline ratio of the energy storage system cost; The annual equipment scrap residual value recovery cost is expressed as follows: In the formula, δ is the proportion of the recovered part in the battery energy storage system; γ is the equipment scrap residual value recovery cost coefficient; β is the βth replacement of part of the battery energy storage.

4. The multi-type energy storage optimal configuration method considering the coordinated support of electric power and electricity quantity according to claim 1, wherein The energy storage state of charge constraint is expressed as follows: Wherein, are the initial state of charge of the battery energy storage system and the power-type energy storage system respectively; are the state of charge of the battery energy storage system and the power-type energy storage system at time t respectively; are the output power of the battery energy storage system and the power-type energy storage system at time t respectively; are the rated capacities of the battery energy storage system and the power-type energy storage system respectively; are the minimum and maximum state of charge of the battery energy storage system; The minimum energy storage configuration constraint is expressed as follows: Wherein, is the total power and total capacity requirements of the multi-type energy storage system in the inertia support mode and the primary frequency regulation mode at time t; is the output power and output power of the battery energy storage system at time t; is the output power and output power of the power-type energy storage system at time t; is the inertia support output power; is the primary frequency regulation output power; ξ k is the control coefficient of the inertia support mode and the primary frequency regulation mode; SOC is the SOC value of the multi-type energy storage system; The power constraint of the multiple types of energy storage systems is expressed as follows: Wherein, are respectively the output power and rated power of the battery energy storage system at the current moment; are respectively the output power and rated power of the power-type energy storage system at the current moment; The curtailment rate constraint is expressed as follows: In the formula, is the loss power when curtailment occurs in the new energy power station throughout the year; is the output power of the new energy power station throughout the year; t is the time when curtailment occurs within one year. The total charge-discharge power balance constraint of the multiple types of energy storage systems with the battery energy storage system and the power-type energy storage system is expressed as follows: P ESS_ch = P bess_ch + P pow_ch P ESS_disch = P bess_disch + P pow_disch Where, P ESS_ch , P bess_ch , P pow_ch are the charging powers of the multi-type energy storage system, battery energy storage system, and power-type energy storage system respectively; P ESS_disch , P bess_disch , P pow_disch are the discharging powers of the multi-type energy storage system, battery energy storage system, and power-type energy storage system respectively.

5. The multi-type energy storage optimal configuration method considering the coordinated support of electric power and electricity quantity according to claim 1, characterized in that The solving of the pre-established capacity optimization configuration model of the multiple types of energy storage systems on the new energy side is specifically as follows: Using the particle swarm algorithm to solve the pre-established capacity optimization configuration model of the multiple types of energy storage systems on the new energy side, including: Randomly generate an optimal configuration plan for the capacity of the energy storage system on the new energy side, specifically initialize the velocity and position parameters of the particles; Select the objective function and constraint conditions and update the velocity and position parameters of the particles; Continuously iterate the velocity and position parameters of the particles to obtain the individual optimal solution and the global optimal solution, and finally obtain the optimal solution for the capacity optimization configuration of the multi-type energy storage system.

6. A multi-type energy storage capacity optimization and configuration system considering source-storage collaborative support using the method according to any one of claims 1-5, characterized in that, It includes: Operation parameter acquisition module: used to acquire the operation parameters of the new energy power station and the multi-type energy storage system; wherein, the multi-type energy storage system is configured on the new energy power station side; Optimization configuration module: used to solve the pre-established capacity optimization configuration model of the multi-type energy storage system on the new energy side according to the operation parameters of the new energy power station and the multi-type energy storage system, obtain the rated capacity and rated power of the multi-type energy storage system, and select the optimal configuration plan for the capacity of the multi-type energy storage system on the new energy power station side with the maximum annual power generation of the new energy power station and the maximum annual net income of the multi-type energy storage system during the planning period of the new energy power station as the comprehensive goal.

7. The multi-type energy storage capacity optimization and configuration system considering source-storage collaborative support according to claim 6, wherein The operation parameters of the new energy power station and the multi-type energy storage system include the output values, prediction values, cost coefficients, replacement times of each component in the new energy power station and the multi-type energy storage system, and the operation years of the new energy power station.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it realizes the steps of the multi-type energy storage optimization configuration method considering the coordinated support of electric power and electricity quantity according to any one of claims 1 to 5.

Images