Energy optimization method and system for renewable energy coupled pumped storage system

Abstract

The present invention discloses an energy optimization method and system for a renewable energy coupled pumped storage system, comprising: taking minimum life cycle cost and power loss rate as evaluation targets of a hybrid system; obtaining required power and output power of renewable energy within a time period, and controlling the operation strategy and operation power of an electric pump unit or a water turbine unit according to a comparison result between the output power of the renewable energy and the required power; obtaining energy supply power according to the output power of the renewable energy and the operation power of the electric pump unit or the water turbine unit, and when the energy supply power is less than the required power, determining that the operation strategy of the current time period does not meet the required power, and updating the power loss rate according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, until the number of iterations reaches a preset number; and sorting the operation strategy and the power loss rate of each time period according to the evaluation target, thereby obtaining the optimal operation strategy of the hybrid system.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply systems, and in particular to an energy optimization method and system for a renewable energy coupled pumped storage system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The combination of renewable energy and energy storage systems provides new opportunities for electricity consumption. The main function of energy storage systems in renewable energy systems is to perfectly compensate for the mismatch between electricity demand and electricity supply when renewable energy cannot meet the load demand. Therefore, in order to improve the reliability and stability of electricity in renewable energy applications, the development of economically viable energy storage remains a huge and important challenge, especially for those independent renewable energy sources that are fully powered by intermittent solar and wind power.

[0004] Each energy storage technology has special characteristics that make it consistent only with specified application scenarios. Therefore, it is necessary to choose the right storage technology that matches the specific application. There are a variety of energy storage technologies for fixed power applications, which can be classified according to the form of energy storage, the duration of energy storage (long-term, short-term energy storage), or other criteria (such as maturity, capital cost, efficiency), etc. For example, they are classified by energy storage method: mechanical energy storage, such as pumped storage, compressed air energy storage, flywheel, etc.; electrochemical energy storage, such as batteries, flow batteries, metal air batteries, hydrogen fuel cells and solar fuels; electromagnetic energy storage, such as supercapacitors and superconducting magnetic energy storage; and thermal energy storage. Among them, the first three groups are mostly used in power systems. With the advancement of energy storage technology, almost all energy storage technologies can be applied at small and large scale levels.

[0005] By comparing the storage technology characteristics of small-scale systems in terms of technical priority, cost-effectiveness, efficiency, and storage duration, micro pumped hydro storage can be considered as suitable for medium- and long-term storage deployed in renewable energy systems.

[0006] Most of the existing energy storage system design, calculation and optimization methods are aimed at matching, optimizing design and calculation of energy system energy load. For renewable energy coupled pumped storage system, its energy form is more complex. In addition to the conventional energy system energy load matching, technical and economic performance indicators such as system investment cost, life cycle cost, power failure rate, etc. will become key factors and important indicators for evaluating and measuring the feasibility and practicality of engineering technology.

[0007] The calculation of existing mathematical models for multi-objective optimization problems is mainly based on theoretical analysis. However, for hybrid systems involving renewable energy power supply coupled with micro pumped storage systems, the actual engineering parameters and boundary conditions are practical and discrete, and are restricted by the specifications of existing equipment, products, technologies, etc. For example, the number of photovoltaic modules, the number of wind turbines, the installation height of the upper reservoir, and many other variables. Therefore, it is impossible to directly apply mathematical theoretical models for multi-objective optimization solutions. Summary of the invention

[0008] In order to solve the above problems, the present invention proposes an energy optimization method and system for a renewable energy coupled pumped storage system, taking the minimum life cycle cost and power loss rate as the evaluation targets of the hybrid system of the renewable energy coupled pumped storage system to obtain the optimal operation strategy of the hybrid system.

[0009] In order to achieve the above object, the present invention adopts the following technical solution:

[0010] In a first aspect, the present invention provides an energy optimization method for a renewable energy coupled pumped storage system, comprising:

[0011] Taking the minimum life cycle cost and power loss rate as the evaluation objectives of the hybrid system of renewable energy coupled pumped storage system, the power loss rate is calculated for the candidate operation strategies, and the candidate operation strategies are evaluated according to the evaluation objectives to obtain the optimal operation strategy of the hybrid system;

[0012] The process of calculating the power loss rate for the candidate operation strategy includes: initializing the power loss rate, obtaining the required power and the output power of the renewable energy in the time period for each operation strategy, and controlling the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power;

[0013] The supply power is obtained based on the output power of renewable energy and the operating power of the electric pump unit or the turbine unit. When the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power. The power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods until the number of iterations reaches the preset number, and the power loss rate of the current operation strategy is obtained.

[0014] As an optional implementation, the operation strategy includes: the number of photovoltaic modules, the number of wind turbines, the height of the reservoir, the volume of the reservoir, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine unit, the nominal capacity of the electric pump unit and the energy release capacity.

[0015] As an optional implementation method, if the output power of renewable energy is greater than the demand power, the excess power is determined, and the allowable charging power range is obtained according to the operating constraints of the electric pump unit and the reservoir storage capacity; based on the comparison between the excess power and the allowable charging power range, the operating strategy and operating power of the electric pump unit are controlled.

[0016] As an optional implementation, if the excess power is within the allowable charging power range, the electric pump unit operates at the excess power; if the excess power is greater than the maximum allowable power, the electric pump unit operates at the maximum allowable power; if the excess power is less than the minimum allowable power, the electric pump unit is shut down.

[0017] As an optional implementation method, if the output power of renewable energy is less than the required power, the power shortage is determined, and the allowable discharge power range is obtained according to the operating constraints of the turbine and the available water in the reservoir; based on the comparison between the power shortage and the allowable discharge power range, the operating strategy and operating power of the turbine unit are controlled.

[0018] As an optional embodiment, if the insufficient power is within the allowable discharge power range, the turbine will be allowed to operate at the insufficient power; if the insufficient power is lower than the minimum allowable discharge power, the turbine will operate at the minimum allowable discharge power; if the insufficient power is higher than the maximum allowable discharge power, the turbine will operate at the maximum allowable discharge power.

[0019] As an optional implementation, after the operation of the electric pump unit or the water turbine unit is completed, the water head in the reservoir is updated according to the discharge flow of the water turbine unit or the charge flow of the electric pump unit.

[0020] In a second aspect, the present invention provides an energy optimization system for a renewable energy coupled pumped storage system, comprising:

[0021] The optimization module is configured to use the minimum life cycle cost and the power loss rate as evaluation targets of the hybrid system of the renewable energy coupled pumped storage system, calculate the power loss rate for the candidate operation strategies, and evaluate the candidate operation strategies according to the evaluation targets to obtain the optimal operation strategy of the hybrid system;

[0022] The power loss rate calculation module is configured to initialize the power loss rate, obtain the required power and the output power of the renewable energy in the time period for each operation strategy, and control the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power;

[0023] The update module is configured to obtain the supply power based on the output power of renewable energy and the operating power of the electric pump unit or the turbine unit. When the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power, and the power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, until the number of iterations reaches a preset number, and the power loss rate of the current operation strategy is obtained.

[0024] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in the first aspect is performed.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions, wherein when the computer instructions are executed by a processor, the method described in the first aspect is performed.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present invention proposes a hybrid system of renewable energy power supply coupled with a micro pumped storage system. It combines the renewable energy power supply characteristics with the micro pumped storage system characteristics, and conducts engineering system modeling and calculation for multiple variables such as the number of photovoltaic modules, the number of wind turbines, the installation height of the upper reservoir, the reservoir volume, the pipe diameter, the reservoir depth-diameter ratio, the turbine capacity, and the pump capacity of the hybrid system. It is necessary to combine the renewable energy power supply characteristics with the micro pumped storage system characteristics, and conduct multi-objective optimization in combination with feasible engineering participation of the hybrid system. The present invention proposes an energy optimization method and system for a renewable energy power supply coupled with a pumped storage system. By considering technical and economic performance indicators such as investment cost, life cycle cost, and power failure rate, it compares and evaluates the technical and economic performance, levelized energy cost, probability of power supply loss, monthly and annual oversupply, and annual ratio of renewable energy to supplied power of the hybrid system of a renewable energy power supply coupled with a micro pumped storage system. By considering a wide range of input variables, including: number of PV panels, number of wind turbines, upper reservoir installation height, reservoir volume, pipe diameter, reservoir depth-diameter ratio, turbine capacity, pump capacity, etc.; the non-dominated sorting genetic algorithm is linked to the direct steady-state operation strategies of PV-pumped storage and PV-wind-pumped storage, providing detailed and useful information for the optimal design of pumped storage systems based on renewable energy.

[0028] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0030] Figure 1 This is a flow chart of the energy optimization method for a renewable energy coupled pumped storage system provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0032] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0033] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0035] Example 1

[0036] Small-scale energy systems with an expected capacity of less than 1MW are systems that can provide energy to buildings, small areas or limited communities. This application scenario of renewable energy systems and energy storage systems has very broad application prospects on small islands. Among all energy storage technologies, flywheels, supercapacitors and superconducting magnetic energy storage are only suitable for short-term storage in power and energy applications. Although these technologies are characterized by high efficiency and long cycle life, their energy density is low, which makes these energy storage technologies costly per unit of energy and have a relatively high self-discharge rate. On the other hand, batteries, micro pumped storage, hydrogen fuel cells and micro compressed air energy storage are generally considered as medium / long-term storage technologies in stationary applications. In addition, in terms of storage technology priorities for small-scale energy storage, batteries (lead acid, lithium-ion, NaS, NiCd), micro pumped storage and flywheels (for short-term storage only) are the most mature technologies. Therefore, the implementation of these storages may face fewer problems.

[0037] By comparing the storage technology characteristics of small systems in terms of technical priority, cost-effectiveness, efficiency and storage time, micro pumped storage can be considered as suitable for medium- and long-term storage deployed in renewable energy systems. On the other hand, pumped storage integrated renewable energy is popular due to its low maintenance cost, long life, extremely low unit energy cost and environmental friendliness; it can also be used in various scales in hybrid power generation systems, namely large, small, micro and pico. The capacity of small pumped storage can reach several megawatts; the capacity of micro pumped storage can reach 100 kilowatts; and the capacity of pico pumped storage is less than 5kW. Micro pumped storage can be implemented to provide continuous electricity to remote or small communities when solar photovoltaic and wind energy systems cannot meet the demand.

[0038] PV-pumped storage systems are flexible in design and construction and can provide continuous power supply to mountainous areas. By evaluating the possibility of upgrading hydroelectric power plants with solar generators, PV-pumped storage systems, although more expensive than single pumped storage systems, are more suitable for energy markets due to their greater power generation flexibility. A techno-economic assessment of small-scale hybrid PV-pumped storage systems on islands shows that this technology is very promising in terms of long-term sustainability and environmental protection.

[0039] The feasibility and optimal design of an autonomous solar-wind pumped storage power supply system for isolated microgrids are presented, considering the efficiency of each subsystem against the operating conditions (wind speed, solar irradiance and pumped storage at partial load), demonstrating that a renewable energy system based on pumped storage can support 100% of the energy of remote communities. The operation of a large-scale solar-wind hybrid system coupled with pumped storage is simulated and optimized, and the local consumption index is introduced as a measure of the distribution network costs associated with centralized generation, which is beneficial to the increase of the share of renewable energy.

[0040] Currently, few studies have been conducted to comparatively evaluate the techno-economic optimal design of micro pumped hydro for stand-alone renewable energy supply systems by considering techno-economic performance indicators such as investment cost, life cycle cost, levelized cost of energy, probability of power supply loss, monthly and annual oversupply, and annual ratio of renewable energy to supplied electricity. The evaluation and comparison of energy storage based on renewable energy systems is divided into two options: the first is based on photovoltaic alone and the second on photovoltaic wind energy, studying how wind, solar and the best combination of both provide a certain degree of smoothing in the case study, and how their optimal ratio affects the system cost and the optimal storage capacity.

[0041] To this end, this embodiment provides an energy optimization method for a renewable energy coupled pumped storage system, comprising:

[0042] Taking the minimum life cycle cost and power loss rate as the evaluation objectives of the hybrid system of renewable energy coupled pumped storage system, the power loss rate is calculated for the candidate operation strategies, and the candidate operation strategies are evaluated according to the evaluation objectives to obtain the optimal operation strategy of the hybrid system;

[0043] The process of calculating the power loss rate for the candidate operation strategy includes: initializing the power loss rate, obtaining the required power and the output power of the renewable energy in the time period for each operation strategy, and controlling the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power;

[0044] The supply power is obtained based on the output power of renewable energy and the operating power of the electric pump unit or the turbine unit. When the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power. The power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods until the number of iterations reaches the preset number, and the power loss rate of the current operation strategy is obtained.

[0045] In this embodiment, the operation strategy includes the number of photovoltaic modules, the number of wind turbines, the height of the reservoir, the volume of the reservoir, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine unit, the nominal capacity of the electric pump unit and the energy release capacity.

[0046] In this embodiment, the hybrid system of the renewable energy system coupled with the pumped storage system includes a renewable energy part of photovoltaic / wind energy and an energy storage part, which mechanically stores the extra energy generated by the photovoltaic / wind energy part by charging and storing water in the upper reservoir, and then when needed (for example, when there is no sunshine or no wind), the stored water is transported downward to drive the turbine set to generate electricity.

[0047] In this embodiment, the photovoltaic system is equipped with dual-axis solar tracking technology. The dual-axis tracker has an advantage of between 17.7% and 31.2% over fixed panels in terms of solar gain. The dual-axis tracker is able to increase the yield by 25-26%. This technology always maintains the normal direction to the sun, so it produces the most power due to receiving the highest global irradiance compared to a fixed position, i.e. a tilted photovoltaic system; the modular structure of the photovoltaic system has considerable advantages, and more panels can be added as needed.

[0048] In this embodiment, a centrifugal pump is considered, which is simulated based on the pump power equation, which expresses the dependence of the pump power on efficiency, flow rate and total head. The total head is the sum of the static head and friction head losses. The friction head losses and the friction factor are calculated based on the Colebrook equation. The pump is restricted to operate within the permissible power range by considering the operating range of the pump and avoiding reservoir overflow. The filling pipe length (or static head) is considered to be equal to the sum of the reservoir installation height and the reservoir depth, and the discharge pipe length is equal to the reservoir installation height. By considering the operating range of the turbine and the available water in the reservoir, it is assumed that the turbine generator operates within the permissible discharge power range. In order to avoid negative water volume in the upper reservoir, the maximum possible discharge flow is calculated based on the available water in the reservoir, and then the corresponding discharge power is calculated. Therefore, the minimum allowable discharge power and the maximum allowable discharge power are calculated, and the head in the reservoir is updated at the end of each time interval.

[0049] In this embodiment, the hybrid system of the renewable energy system coupled with the pumped storage system includes: a separate photovoltaic system coupled with a pumped storage system and a photovoltaic-wind system coupled with a pumped storage system; wherein the photovoltaic-pumped storage system is a photovoltaic system (including photovoltaic components, photovoltaic tracking system, inverter and control panel) and mechanical energy storage, namely hydropower storage (including motor pump, turbine generator, charging and discharge pipes, upper reservoir); the photovoltaic-wind-water energy storage system considers the combination of photovoltaic and wind turbines (including wind turbines, wind turbine towers, inverters and control panels) with mechanical energy storage.

[0050] In this embodiment, decision variables, objective functions and technical performance indicators of a hybrid system of renewable energy coupled with a pumped storage system are constructed;

[0051] The specific decision variables are: the number of photovoltaic modules N 光伏 , Number of fans N 风能 , upper reservoir installation height H, reservoir volume V, filling and discharge pipe diameter D, reservoir depth L, reservoir depth-diameter ratio Turbine nominal capacity Pump nominal capacity Battery storage capacity 蓄能 , battery discharge capacity d 放能 ; In the photovoltaic coupled pumped storage system, the number of wind turbines N is not considered 风能 , whereas in the photovoltaic-wind-pumped storage system, all the above variables are considered.

[0052] Constraints are set for each of the above variables and defined in their respective search spaces, namely:

[0053]

[0054] F=Min(f1(X1,X2,…X n ),f2(X1,X2,…X n ))

[0055] Among them, X i represents one of the above variables, and Indicates the lower and upper limits of a variable.

[0056]

[0057]

[0058]

[0059] R 串联 =R 串联标态 ;

[0060] Among them, I 水库 is the photovoltaic current of the reservoir (A); I 光电 is the current in a photovoltaic module (A); I 光电饱和 is the saturation current (A) in a photovoltaic module; I 光电标态 is the current (A) in a photovoltaic module under standard conditions; V 水库 is the photovoltaic voltage of the reservoir (V); V 热 is the diode thermal voltage (V); N 光伏 is the total number of PV panels; N 并联 is the number of photovoltaic cells connected in parallel in a module; N 串联 is the number of photovoltaic cells connected in series in a module; R 串联 is the series resistance (Ω); R 并联 is the shunt / parallel resistance (Ω); R 并联标态 is the parallel resistance under standard operating conditions (Ω); R 串联标态 is the series resistance under standard operating conditions (Ω); α 短流 is the short-circuit current relative temperature coefficient (% / K); T 电池 is the battery temperature; T 标态 is the temperature of the battery under standard operating conditions; G is the radiation (W / m2); G 标态 It is the radiation under standard operating conditions (W / m2).

[0061] In this embodiment, the minimum life cycle cost C 总 and power loss rate η 失电率 The evaluation target is life cycle cost C 总 It is a method of evaluating the total cost of ownership of mechanical equipment. 总Analysis is the best way to compare the economic performance of systems and therefore determine which of the proposed alternatives is the most economically attractive. 总 The calculation of the life cycle cost C takes into account the initial investment cost, maintenance cost, operating cost and residual value related to the entire life cycle. In order to convert all cash flows during the life cycle of the system into present value, the life cycle cost C 总 The analysis method uses a discount rate. Power loss rate η 失电率 Defined as the percentage of time intervals in which the required power is not fully met to the total number of time intervals; specifically:

[0062] C 总 =C 投资 +C 维修 +C 运行 -C 残值

[0063]

[0064]

[0065] Among them, P 可再生供电 is the power supplied by renewable energy, N is the total number of time intervals, P 水轮机 is the turbine power, P 需求 is the required power, C 投资 , C 维修 , C 运行 , C 残值 They are investment cost, maintenance cost, operating cost and residual value respectively; C 光伏 , C 风能 , C 可再生 , C 泵 , C 水轮机 , C 管道 They are the costs of photovoltaic operation, wind power generation, renewable energy, pumps, turbines, and pipelines.

[0066] In this embodiment, two performance indicators are also included, namely, η 供需比 and η 可再生占比 ; η 供需比 It is an indicator of the matching degree of energy supply and demand, which indicates the ratio of energy supplied by the system monthly or annually to the energy required by demand; when η 供需比 When it is close to 1, there is a maximum match between electricity supply and electricity demand. 可再生占比 is the ratio of the monthly or annual energy provided to the demand side by renewable energy (i.e. PV or PV-wind) to the total energy provided by the system; in other words, η 可再生占比 It is an indicator showing how much of the energy required for demand is provided by renewable energy. Specifically:

[0067]

[0068]

[0069] In this embodiment, a modified non-dominated sorting genetic algorithm is linked to an operating strategy to solve the current multi-objective optimization problem to simultaneously minimize the life cycle cost and power loss rate of the system. The selection of a suitable optimization tool is highly relevant to the problem being studied. Genetic algorithm is a random search method that mimics natural evolution and is well known to be one of the most popular and widely used multi-objective optimization algorithms. Genetic algorithms are simple and do not require gradient data. In addition, it has a better chance of finding the global optimal solution than local search methods. The algorithm is also powerful from the perspective of control parameters.

[0070] The optimization procedure in this embodiment adopts a non-dominated sorting genetic algorithm, which is briefly described as follows:

[0071] (1) Randomly generate an initial population (generation). A population consists of many individuals, each of which represents a solution or a set value of a design parameter.

[0072] (2) Evaluate the objective function of each individual in the generated population;

[0073] The first objective function is:

[0074] C 总 =C 投资 +C 维修 +C 运行 -C 残值 ;

[0075] The second objective function is:

[0076]

[0077] The set values ​​of the design variables of each solution are provided as input to the "operating scenario", and the η of the solution is received from the "operating scenario". 失电率 As output;

[0078] (3) Rank the individuals according to the objective function evaluated; for example, "Solution A" is better than "Solution B", it should be better in at least one objective and not worse in other objective functions; until all individuals (solutions) are ranked, and the individuals in each level are ranked according to the crowding distance (i.e., a measure of solution diversity). In each level, solutions with higher crowding distances are considered preferred solutions for diversity considerations.

[0079] (4) Selection process and mating pool: construct a mating pool from which the mother set is randomly selected to generate a new generation of subsets.

[0080]

[0081] in, represents the number of elite individuals from level λ included in the mating pool, S λ represents the total number of individuals with rank λ, w represents the population size (or the number of individuals in each generation), and θ (0<θ<1) is the geometric distribution factor.

[0082] (5) Reproduction (crossover and mutation): After randomly selecting parents from the mating pool, offspring are produced through a crossover procedure. Crossover produces offspring that inherit characteristic values ​​from the parent set, while mutation changes characteristic values. Mutation makes it possible for the subset to have different characteristic values ​​from the parent set, so the subset may have some characteristic values ​​that are different from the parent set.

[0083] (6) Convergence criteria and control parameters: Repeat the steps described above until convergence.

[0084] In this embodiment, since adjusting the genetic algorithm control parameters will affect the quality of the optimization results, the algorithm is considered to terminate after 300 generations. Therefore, the control parameters of the genetic algorithm (crossover, mutation, number of individuals per generation) are selected after checking different settings.

[0085] In this embodiment, one hour is a time period, one year is the total duration, and a total of 8760 time periods are used. The input data include the number of photovoltaic modules and / or the number of wind turbines, the installation height of the upper reservoir, the reservoir volume, the diameter of the filling and discharge pipes, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine, the nominal capacity of the pump, and the battery capacity. Hourly data of global irradiance, wind speed, temperature, and demand curves can also be input. The output includes hourly data of system operating variables, such as photovoltaic power generation, wind turbine power generation, pumping power, turbine power generation, and the state of charge of the upper reservoir and the state of charge of the battery.

[0086] like Figure 1 As shown in Figure 2, the energy optimization strategy of renewable energy coupled pumped storage system specifically includes the following steps:

[0087] (1) Preset candidate operation strategies, take the minimum life cycle cost and power loss rate as the evaluation objectives of the hybrid system of renewable energy coupled with battery energy storage system, and select the optimal operation strategy from the candidate operation strategies according to the evaluation objectives; wherein the operation strategy includes the number of photovoltaic modules, the number of wind turbines, the height of the reservoir, the volume of the reservoir, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine unit, the nominal capacity of the electric pump unit, and the energy discharge capacity.

[0088] (2) Initializing the time period and power loss rate, setting time period i to 1 and the power loss rate to 0; for each operation strategy, calculating the output power of renewable energy in the time period based on the input data, where the output power of renewable energy is the sum of photovoltaic power and wind power;

[0089] (3) If the output power of the renewable energy source is higher than the required power, the excess power is determined accordingly, i.e., the excess power is obtained by subtracting the required power from the output power of the renewable energy source;

[0090] At this time, considering the operation limitation of the pump and the filling flow rate at the end of the time interval not causing the reservoir to overflow, the allowable charging power range is obtained according to the operation constraint of the electric pump unit and the reservoir capacity.

[0091] Specifically: According to the reservoir capacity, the maximum charge flow rate is obtained, that is, Q p,Max =((Lh t )×A) / 3600, and calculate the corresponding power but:

[0092]

[0093]

[0094] (3-1) If the excess power is within the allowable charging power range, the electric pump unit operates at the excess power and stores water in the upper reservoir.

[0095] (3-2) If the excess power is less than the minimum allowed charging power, the electric pump unit is shut down; the output power of the renewable energy source will be fully delivered to the user (although this will result in oversupply).

[0096] (3-3) If the excess power is greater than the maximum allowable charging power, the electric pump unit operates at the maximum allowable power and transmits the excess power to the user end (although this will cause oversupply).

[0097] (4) If the output power of the renewable energy source is less than the required power, the power deficit is determined based on the required power minus the output power of the renewable energy source;

[0098] At this time, set the constraints considering the turbine operation range and the available water volume of the reservoir, and calculate the allowable discharge power range based on the constraints.

[0099] The constraints are: the turbine operates within a power range of 60-120% of its nominal power; the water discharge rate results in a negative water volume in the reservoir at the end of the time interval;

[0100] Calculate the possible maximum flow Q based on the available water volume in the reservoir t,Max =(h t ×A) / 3600, and calculate the corresponding discharge power The allowable discharge power range is:

[0101]

[0102]

[0103] (4-1) If the underpower is within the allowable discharge power range, the turbine will be allowed to operate at underpower.

[0104] (4-2) If the deficit power is lower than the minimum allowable discharge power, the turbine operates at the minimum allowable discharge power (although this may result in oversupply).

[0105] (4-3) If the negative power is higher than the maximum permissible discharge power, the turbine operates at the maximum permissible power to compensate for the power deficit as much as possible.

[0106] (5) After the electric pump unit or turbine unit has finished running, calculate the discharge flow rate Q of the turbine t Or the charge flow Q of the electric pump unit p , updating the water head in the reservoir.

[0107] (6) After the operation of the electric pump unit or the hydro turbine unit is completed, the energy supply power is obtained according to the output power of the renewable energy and the operating power of the electric pump unit or the hydro turbine unit; specifically, the energy supply power is the sum of the output power of the renewable energy and the operating power of the hydro turbine unit, or the energy supply power is the difference between the output power of the renewable energy and the operating power of the electric pump unit.

[0108] (7) If the supplied power is less than the required power at this time, it is determined that the operation strategy of the current time period does not meet the required power. The power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, and the next time period is entered. After continuous iteration until the last time interval is completed, the power loss rate of the current operation strategy is obtained.

[0109] (8) Sort the operation strategies according to the evaluation objectives to obtain the optimal operation strategy for the hybrid system.

[0110] Example 2

[0111] This embodiment provides an energy optimization system for a renewable energy coupled pumped storage system, including:

[0112] The optimization module is configured to use the minimum life cycle cost and the power loss rate as evaluation targets of the hybrid system of the renewable energy coupled pumped storage system, calculate the power loss rate for the candidate operation strategies, and evaluate the candidate operation strategies according to the evaluation targets to obtain the optimal operation strategy of the hybrid system;

[0113] The power loss rate calculation module is configured to initialize the power loss rate, obtain the required power and the output power of the renewable energy in the time period for each operation strategy, and control the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power;

[0114] The update module is configured to obtain the supply power based on the output power of renewable energy and the operating power of the electric pump unit or the turbine unit. When the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power, and the power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, until the number of iterations reaches a preset number, and the power loss rate of the current operation strategy is obtained.

[0115] It should be noted that the above modules correspond to the steps described in Example 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 1. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer executable instructions.

[0116] In further embodiments, there is also provided:

[0117] An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in Embodiment 1 is performed. For the sake of brevity, it will not be described in detail here.

[0118] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0119] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0120] A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the method described in Example 1 is completed.

[0121] The method in Example 1 can be directly embodied as a hardware processor, or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it is not described in detail here.

[0122] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in conjunction with this embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0123] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. An energy optimization method for renewable energy coupled micro pumped storage system, characterized in that: include: Taking the minimum life cycle cost and power loss rate as the evaluation objectives of the hybrid system of renewable energy coupled pumped storage system, the power loss rate is calculated for the candidate operation strategies, and the candidate operation strategies are evaluated according to the evaluation objectives to obtain the optimal operation strategy of the hybrid system; The renewable energy sources are photovoltaic and wind energy; The process of calculating the power loss rate for the candidate operation strategy includes: initializing the power loss rate, obtaining the required power and the output power of the renewable energy in the time period for each operation strategy, and controlling the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power; The supply power is obtained according to the output power of the renewable energy and the operating power of the electric pump unit or the turbine unit. When the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power, and the power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, until the number of iterations reaches a preset number, and the power loss rate of the current operation strategy is obtained; The operation strategy includes: the number of photovoltaic modules, the number of wind turbines, the height of the reservoir, the volume of the reservoir, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine unit, the nominal capacity of the electric pump unit and the energy release capacity; The power loss rate is the percentage of the time interval in which the required power is not fully met to the total time interval; The minimum life cycle cost and power loss rate are simultaneously minimized by a non-dominated sorting genetic algorithm; The non-dominated sorting genetic algorithm is specifically: Randomly generate an initial population, a population consists of several individuals, each of which represents a solution or a set value of a design parameter; Evaluate the objective function of each individual in the generated population; The first objective function is: ； in, is the life cycle cost, They are investment cost, maintenance cost, operating cost and residual value; The second objective function is: ； Among them, η 失电率 is the power loss rate, Powering renewable energy sources, is the turbine power, is the required power, T is the time, N is the total number of time intervals, is the total time; The set values ​​of the design variables of each solution are provided as input to the operating scenario, and the solution receives the set values ​​from the operating scenario. As output; The individuals are ranked according to the evaluated objective function until all individuals are ranked, and the individuals in each rank are ranked according to the crowding distance; in each rank, the solution with a higher crowding distance is considered the preferred solution; Selection process and mating pool: construct a mating pool from which the mother set is randomly selected to produce the new generation of subsets; ； in, represents the number of elite individuals from level λ included in the mating pool, represents the total number of individuals with rank λ, w represents the population size, θ is the geometric distribution factor, 0<θ<1; Reproduction: After randomly selecting parents from the mating pool, offspring are produced through a crossover procedure; crossover produces inherited characteristic values ​​from the parent set, mutation changes characteristic values, and mutation makes the subset have a certain probability of having a different characteristic value from the parent set; Convergence criteria and control parameters: Repeat the steps described above until convergence; If the output power of renewable energy is greater than the required power, the excess power is determined, and the allowable charging power range is obtained according to the operating constraints of the electric pump unit and the reservoir storage capacity; according to the comparison between the excess power and the allowable charging power range, the operation strategy and operating power of the electric pump unit are controlled; if the excess power is within the allowable charging power range, the electric pump unit operates at the excess power; if the excess power is greater than the maximum allowable power, the electric pump unit operates at the maximum allowable power; if the excess power is less than the minimum allowable power, the electric pump unit is shut down; If the output power of renewable energy is less than the required power, the power shortage is determined, and the allowable discharge power range is obtained according to the operating constraints of the turbine and the available water volume of the reservoir; based on the comparison between the power shortage and the allowable discharge power range, the operating strategy and operating power of the turbine unit are controlled; if the power shortage is within the allowable discharge power range, the turbine will be allowed to operate at the power shortage; if the power shortage is lower than the minimum allowable discharge power, the turbine will operate at the minimum allowable discharge power; if the power shortage is higher than the maximum allowable discharge power, the turbine will operate at the maximum allowable discharge power.

2. The energy optimization method for a renewable energy coupled micro pumped storage system according to claim 1, characterized in that: After the operation of the electric pump unit or the turbine unit is completed, the water head in the reservoir is updated according to the discharge flow of the turbine unit or the charge flow of the electric pump unit.

3. An energy optimization system for coupling renewable energy to a micro pumped storage system, characterized in that: include: The optimization module is configured to use the minimum life cycle cost and power loss rate as the evaluation target of the hybrid system of the renewable energy coupled pumped storage system, calculate the power loss rate for the candidate operation strategy, and evaluate the candidate operation strategy according to the evaluation target to obtain the optimal operation strategy of the hybrid system; the renewable energy is photovoltaic and wind energy; The power loss rate calculation module is configured to initialize the power loss rate, obtain the required power and the output power of the renewable energy in the time period for each operation strategy, and control the operation strategy and operation power of the electric pump unit or the water turbine unit according to the comparison result between the output power of the renewable energy and the required power; An updating module is configured to obtain the supply power according to the output power of the renewable energy and the operating power of the electric pump unit or the water turbine unit, and when the supply power is less than the required power, it is determined that the operation strategy of the current time period does not meet the required power, and the power loss rate is updated according to the percentage of the number of time periods that do not meet the required power in the total number of time periods, until the number of iterations reaches a preset number, and the power loss rate of the current operation strategy is obtained; The operation strategy includes: the number of photovoltaic modules, the number of wind turbines, the height of the reservoir, the volume of the reservoir, the depth-to-diameter ratio of the reservoir, the nominal capacity of the turbine unit, the nominal capacity of the electric pump unit and the energy release capacity; The power loss rate is the percentage of the time interval in which the required power is not fully met to the total time interval; The minimum life cycle cost and power loss rate are simultaneously minimized by a non-dominated sorting genetic algorithm; The non-dominated sorting genetic algorithm is specifically: Randomly generate an initial population, a population consists of several individuals, each of which represents a solution or a set value of a design parameter; Evaluate the objective function of each individual in the generated population; The first objective function is: ； in, is the life cycle cost, They are investment cost, maintenance cost, operating cost and residual value; The second objective function is: ； Among them, η 失电率 is the power loss rate, Powering renewable energy sources, is the turbine power, is the required power, T is the time, N is the total number of time intervals, is the total time; The set values ​​of the design variables of each solution are provided as input to the operating scenario, and the solution receives the set values ​​from the operating scenario. As output; The individuals are ranked according to the evaluated objective function until all individuals are ranked, and the individuals in each rank are ranked according to the crowding distance; in each rank, the solution with a higher crowding distance is considered the preferred solution; Selection process and mating pool: construct a mating pool from which the mother set is randomly selected to produce the new generation of subsets; ； in, represents the number of elite individuals from level λ included in the mating pool, represents the total number of individuals with rank λ, w represents the population size, θ is the geometric distribution factor, 0<θ<1; Reproduction: After randomly selecting parents from the mating pool, offspring are produced through a crossover procedure; crossover produces inherited characteristic values ​​from the parent set, mutation changes characteristic values, and mutation makes the subset have a certain probability of having a different characteristic value from the parent set; Convergence criteria and control parameters: Repeat the steps described above until convergence; If the output power of renewable energy is greater than the required power, the excess power is determined, and the allowable charging power range is obtained according to the operating constraints of the electric pump unit and the reservoir storage capacity; according to the comparison between the excess power and the allowable charging power range, the operation strategy and operating power of the electric pump unit are controlled; if the excess power is within the allowable charging power range, the electric pump unit operates at the excess power; if the excess power is greater than the maximum allowable power, the electric pump unit operates at the maximum allowable power; if the excess power is less than the minimum allowable power, the electric pump unit is shut down; If the output power of renewable energy is less than the required power, the power shortage is determined, and the allowable discharge power range is obtained according to the operating constraints of the turbine and the available water volume of the reservoir; based on the comparison between the power shortage and the allowable discharge power range, the operating strategy and operating power of the turbine unit are controlled; if the power shortage is within the allowable discharge power range, the turbine will be allowed to operate at the power shortage; if the power shortage is lower than the minimum allowable discharge power, the turbine will operate at the minimum allowable discharge power; if the power shortage is higher than the maximum allowable discharge power, the turbine will operate at the maximum allowable discharge power.

4. An electronic device, characterized in that: The invention comprises a memory and a processor and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method according to any one of claims 1 or 2 is completed.

5. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the method described in any one of claims 1 or 2.

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