CN-115833244-B - Economical dispatching method for wind-light-hydrogen-storage system

Abstract

The invention relates to an economic dispatching method of a wind-light-hydrogen-storage system, which takes two energy storage modes of a battery and hydrogen production into consideration, stores surplus wind energy and light energy, utilizes the battery to discharge and regulate the balance of power when the load power is insufficient, analyzes the operation characteristics of a hydrogen production device, coordinately controls the two energy storage modes by dividing the operation interval of the hydrogen production device, and optimally solves the wind-light-hydrogen-storage system under the condition of solar wind, light and load data to finally obtain a solar power distribution plan of the battery and hydrogen production, thereby realizing the economic dispatching of the system. The energy storage battery and the hydrogen production energy storage mode are utilized to absorb surplus power, operation benefits are obtained by selling hydrogen while reducing waste wind and waste light, the energy storage battery is utilized to discharge and supplement load power, and coordinated control is carried out on the two energy storage modes, so that the economical efficiency of the system can be improved, and the generated energy can follow a load curve as much as possible.

Inventors

• MEI CHUNXIAO
• LI LIANBING
• GAO GUOQIANG
• TAN JIANXIN
• LU SHENGXIN
• ZHANG QINGQING
• ZHANG GUOFENG
• WU WEIQIANG
• LI RUI
• YIN JUNJIE
• CHEN CHENG

Assignees

• 河北工业大学
• 河北建投海上风电有限公司

Dates

Publication Date

20260512

Application Date

20221202

Claims (6)

1. 1. The economic dispatching method of the wind-light-hydrogen-storage system is characterized by taking two energy storage modes of a battery and hydrogen production into consideration, storing surplus wind energy and light energy, and regulating the balance of power by utilizing the discharge of the battery when the load power is insufficient; Performing coordinated control on wind-light-hydrogen-storage system under solar wind, light and load data to perform optimization solution, and finally obtaining a solar power distribution plan of batteries and hydrogen production, thereby realizing economic dispatch of the system; the specific process for carrying out coordinated control on two types of energy storage through dividing the operation interval of the analysis hydrogen production device is as follows: step 3-1, the hydrogen production device is an alkaline electrolytic tank, the battery is a lithium iron phosphate battery, the efficiency characteristic of the alkaline electrolytic tank is analyzed, and the operation efficiency of the alkaline electrolytic tank is expressed as a formula (17): Wherein eta is the operation efficiency of the alkaline electrolytic cell, V th is the thermal neutral potential, and V th ＝1.48V;V cell is the input voltage of the alkaline electrolytic cell under standard conditions; After the operation efficiency of the alkaline electrolytic cell is obtained, drawing a power-efficiency curve by using drawing software, and determining an optimal operation interval of the alkaline electrolytic cell by considering two factors of efficient operation and hydrogen production of the alkaline electrolytic cell aiming at the power-efficiency curve; And 3-2, setting a system operation control strategy by taking economic optimization as a target: Step 3-2-1, when the wind-solar power generation power is larger than the local load power P load (t) and the upper limit power of the operation of the alkaline electrolytic cell The sum of, i.e When the charge state of the lithium iron phosphate battery is more than 0.5, namely The residual electric quantity C soc (t),C s is the capacity of the lithium iron sulfate battery, and the upper power limit of the alkaline electrolytic tank is set to run, namely The residual power P SB is absorbed by the lithium iron phosphate battery, when the charge state of the lithium iron phosphate battery is less than or equal to 0.5, namely At 0.5, the operating power range of the electrolytic tank is set as The residual power is absorbed by the lithium iron phosphate battery; step 3-2-2, when the wind-solar power generation power is larger than the sum of the local load power and the lower limit power of the operation of the alkaline electrolytic cell and smaller than or equal to the sum of the local load power and the upper limit power of the operation of the alkaline electrolytic cell, namely When the operation power range of the alkaline electrolytic tank is set as The residual power or insufficient power is absorbed or supplemented by the lithium iron phosphate battery; Step 3-2-3, when the wind-solar power generation power is less than or equal to the sum of the local load power and the lower limit power of the operation of the alkaline electrolytic cell, namely When the load is supplied, the lower power limit of the alkaline electrolytic tank is set, namely The insufficient power is supplemented by discharging the storage battery; wherein, P Wind (t) is the output power of the wind driven generator model, and P PV (t) is the output power of the photovoltaic cell model.
2. 2. The wind-light-hydrogen-storage system economic dispatch method of claim 1, wherein the dispatch method comprises the steps of: step one, establishing a new energy system mathematical model comprising a fan, a photovoltaic cell, an energy storage battery and a hydrogen production device, wherein the energy storage battery is selected as a lithium iron phosphate battery, and the hydrogen production device is an alkaline electrolytic tank; setting an objective function comprising system running cost, operation income and load electricity shortage punishment and adding corresponding limiting conditions, wherein the method specifically comprises the following steps: Step 1, obtaining an objective function to be optimized through superposition of system operation cost, operation income and load electricity shortage punishment of T time periods; Step 2, setting the limit of the running power and the climbing rate for the energy storage battery and the hydrogen production device, and ensuring that the energy storage battery and the hydrogen production device can normally run during scheduling; Analyzing the operation characteristics of the alkaline electrolytic cell to achieve coordinated control of energy storage and the electrolytic cell; Step four, chaotic initialization is carried out on the WSO algorithm by using Tent mapping, the global optimizing capability of the Laiweider flight strategy enhancement algorithm is introduced, and meanwhile, the random swimming strategy enhancement algorithm is introduced to carry out local optimizing, so that an improved WSO algorithm is obtained and is recorded as I-WSO; processing wind, light and load data before the day, namely recording data once every 24 hours a day at intervals, dividing the 24 hours a day into T continuous time periods to obtain a wind-solar combined power and local load graph, and determining the relation between wind-solar power generation power and local load power in different time periods; And then, under the condition that the limiting condition is met, the I-WSO algorithm is used for executing coordination control to carry out optimization solution on the objective function, so that a day-ahead scheduling plan of two energy storage modes of battery and hydrogen production is obtained.
3. 3. The wind-light-hydrogen-storage system economic dispatch method of claim 2, wherein the data is recorded every 10-20 minutes.
4. 4. The wind-light-hydrogen-storage system economic dispatch method of claim 2, wherein the new energy system mathematical model comprises the following: step 1-1, establishing an equivalent mathematical model of the power generation unit: step 1-1-1, establishing a wind driven generator model, wherein the output power P Wind (t) is shown as formula (1): Wherein V (t) is the wind speed of the t period, V in is the cut-in wind speed, V out is the cut-out wind speed, V ra is the rated wind speed, and P ra is the rated power of the fan; Step 1-1-2, building a photovoltaic cell model, wherein the output power P PV (t) is represented by the formula (2): Wherein P st is the output power of the photovoltaic cell under the standard test condition, K D is the derating factor of the photovoltaic cell, G act (T) is the actual illumination intensity in the T period, G st is the illumination intensity under the standard test condition, alpha is the power temperature coefficient, T w is the working temperature of the panel, and T r is the reference temperature; step 1-2, establishing an equivalent mathematical model of the energy storage unit: Step 1-2-1, establishing a lithium iron phosphate battery model, wherein the residual electric quantity C soc (t) is shown as a formula (3): Wherein epsilon is the self-discharge efficiency of the battery, eta - is the discharge efficiency of the battery, eta + is the charge efficiency of the battery, P SB (t) is the battery interaction power in the period of t, wherein P SB (t) <0 represents discharge and P SB (t) >0 represents charge; step 1-2-2, establishing a hydrogen energy storage unit model, wherein the input power is expressed as a formula (5): P cell ＝V cell I cell (5) I cell ＝i den S cell (7) Wherein V cell is the input voltage of the alkaline electrolytic cell, I cell is the input current of the alkaline electrolytic cell, r 1 、r 2 、s、q 1 、q 2 、q 3 is an empirical factor, A is the electrode area, T is the working temperature, I den is the current density, S cell is the electrode area, V rev is the reversible potential, and 1.23V is taken under standard conditions.
5. 5. The wind-light-hydrogen-storage system economic dispatch method of claim 2, wherein the objective function is formula (8): F=min(C om -C ope +C loss ) (8) Wherein F is the total cost of the energy storage and hydrogen production device, C om is the running cost, C ope is the running income, C loss is the load electricity shortage punishment, T is the time period number of one day, D wind 、D PV 、D sb 、D cell is the unit power operation and maintenance cost of a wind driven generator, a photovoltaic cell, a lithium iron phosphate battery and an alkaline electrolytic tank respectively, and C is the unit hydrogen price; The volume of hydrogen produced for period t; q s is penalty factor, P g (t) is t-period generated energy, P s (t) is t-period load electric quantity, P SB (t) is t-period battery interaction power, P PV (t) is photovoltaic cell output power, P Wind (t) wind driven generator output power, and P cell is hydrogen energy storage unit input power; The limiting conditions are as follows: setting the power balance limit to formula (12): P Wind (t)+P PV (t)＝P SB (t)+P cell (t)+P s (t) (12) setting the interactive power limit of the lithium iron phosphate battery as formula (13), the charge state as formula (14), and the periodic operation as formula (15): C soc (0)＝C soc (T) (15) In the formula, The method comprises the steps of setting operation limits of an electrolytic tank as a formula (16) and a formula (17), wherein the lower limit and the upper limit of alternating power of the lithium iron phosphate battery are adopted, the SOC min 、SOC max is the lower limit and the upper limit of the charge state of the lithium iron phosphate battery, the C s is the capacity of the lithium iron sulfate battery, the C soc (t) is the residual electric quantity of the lithium iron phosphate battery, and the operation limits of the electrolytic tank are set as the following formulas: In the formula, Minimum and maximum power for alkaline cell operation; Is the maximum climbing rate of the alkaline electrolytic cell.
6. 6. The wind-light-hydrogen-storage system economic dispatch method of claim 2, wherein the modified WSO algorithm specifically comprises the steps of: Initializing algorithm parameters, wherein the algorithm parameters comprise maximum iteration times I, population scale N, variable space dimension D, variable upper bound x max and variable lower bound x min ; step 4-2, improving a WSO algorithm initialization strategy; Step 4-2-1, randomly generating a value in (0, 1) and marking as z 1 , and d=1; step 4-2 Tent mapping expression is formula (18): Wherein alpha is the number of particles in the chaotic sequence, and rand (0, 1) is a random number in (0, 1); Step 4-2-3, obtaining a chaotic variable z d+1 through Bernoulli transformation on the Tent mapping expression, wherein the chaotic variable z d+1 is shown as a formula (19): Step 4-2-4:d =d+1, judging whether D reaches the variable space dimension D, if so, storing the generated D-dimensional chaotic sequence, otherwise, returning to step 4-2-2, and recalculating the chaotic variable of the next dimension until a D-dimensional chaotic sequence is generated; Step 4-2-5, generating N D-dimensional chaotic sequences Z 1 ,…,Z N by utilizing the steps 4-2-1 to 4-2-4, wherein Z is a sequence formed by Z, namely a chaotic variable, and generating initial positions of a population by using a formula (20), and describing the initial positions as matrix forms as shown in the formula (21): X i ＝x min +(x max -x min )Z i (20), Step 4-3, calculating a global optimal solution X best , and recording k=1; step 4-4, calculating the moving speed of the individual to the prey, and updating a formula such as (22): Where i=1, 2, N; Is a new velocity vector; X best,k is the optimal position obtained in the kth generation; Is a current position vector, X best is a global optimal position, c 1 、c 2 is a random number in (0, 1), p 1 、p 2 represents the strength of a shark individual, mu is a recommended contraction factor, k is the current iteration number, k=1, 2, I, p min 、p max is the minimum and maximum value of p 1 、p 2 , p min ＝0.5,p 2 =1.5, gamma is an acceleration coefficient, gamma=4.125; step 4-5, updating the position of the optimal prey, wherein when the white shark individuals hear the wave sound caused by the prey movement or smell, the position of the optimal prey is updated as follows: In the formula, Is a new individual location; Is a negative operator, a and b are binary vectors, X O represents a logic vector, f represents fluctuation frequency, mv represents movement force, f min 、f max is minimum and maximum fluctuation frequency, and f min ＝0.07,f max ＝0.75;a 0 、a 1 represents two positive numbers for managing exploration and development behaviors; Step 4-6, updating the global optimal solution; Step 4-7, introducing a Laiweighing strategy, introducing the Laiweighing strategy for enhancing the global optimizing capability of the algorithm, reducing the calculation amount of the algorithm, ensuring the optimizing speed of the algorithm, and setting the following strategy to be executed when rand (0, 1) >0.5, otherwise Step 4-8, updating the k+1 generation optimal value, wherein the Lewy flight strategy can enable the individual position to move, but the moving position is not known, and the k+1 generation optimal value is updated according to the following formula: Wherein F (X best,k+1 ) is a value obtained by substituting X best,k+1 into the objective function; Is that Substituting a value obtained by the objective function; Step 4-9, updating the position of the best individual, and when r 3 <S s and i=1, moving the white shark individual to the position of the best individual, updating as follows: In the formula, For updated position, sgn (r 2 -0.5) is used to change the search direction, r 1 、r 2 、r 3 is a random number within (0, 1); A 2 is a positive number for controlling exploration and development, a 2 =0.0005; Step 4-10, updating the position according to the fish school behaviors, wherein when r 3 <S s and i >1, the white shark individuals do not only do the position update to the best individuals according to the formula (35), but also do the fish school behaviors according to the formula (38): Step 4-11, introducing a random walk strategy to enhance the local optimizing capability of the algorithm, calculating X best,k+1 and carrying out random walk treatment on X' best,k+1 ＝X best,k+1 +ε(X k+1,g -X k+1,w ) (40) Wherein X' best,k+1 is an optimal individual of k+1 generation after a random walk strategy is introduced, epsilon is a scaling factor, epsilon-U (0, 1), and X k+1,g 、X k+1,w is two random solutions of k+1 generation; Step 4-12, updating the global optimal solution and the k+1 generation optimal solution: Step 4-13, judging whether the maximum iteration number I is reached or not, if yes, jumping out of the loop to execute step 4-14, otherwise, returning to step 4-4, and updating the position of the optimal prey; Step 4-14, outputting X best 、F(X best ); Step 4-15, processing the day front wind, light and load data, dividing 24 hours a day into 96 time periods, and recording data once every 15 minutes to obtain a wind power generation, photovoltaic power generation and load curve graph; And 4-16, optimizing and solving an objective function by utilizing an I-WSO algorithm under the condition that the limiting condition is met, inputting wind, light and load data, substituting the objective function into the I-WSO algorithm, and iterating to obtain the optimal cost and a day-ahead scheduling plan of the lithium iron phosphate battery and the alkaline electrolytic tank.

Description

Economical dispatching method for wind-light-hydrogen-storage system Technical Field The invention belongs to the field of new energy power system optimization scheduling, and relates to an economic scheduling method of a wind-light-hydrogen-storage system. Background The replacement of traditional fossil energy sources by wind energy, solar energy and other novel energy sources is the key of the current energy source structure transformation, and how to ensure the safe access of the novel energy sources to a power grid, coordinate the output among the energy sources and optimize the economical efficiency of power generation is a precondition for ensuring the long-term development of the power industry. Therefore, the research on the optimal scheduling problem of the new energy system has important significance for the economic and stable operation of the power grid and the improvement of the matching degree of the generated energy and the load. Among the numerous power system optimization scheduling algorithms, intelligent optimization algorithms gradually exhibit their advantages. The white shark optimization algorithm (WHITE SHARK Optimizer, WSO) was proposed by MalikBraik et al in 2022, and is very effective for dealing with multi-limited complex mathematical problems, and the white shark algorithm belongs to a bionic meta-heuristic algorithm, the core concept and basic ideas of which are inspired by the behavior of white sharks during hunting, including their extraordinary hearing and smell during navigation and foraging in the sea, and an equivalent mathematical model is built for foraging behavior to adapt to the full balance of white sharks between exploration and development, and to help search agents explore and develop each potential region of search space to achieve comprehensive and accurate optimization of the proposed problem. The algorithm has novel thought and high policy efficiency. In the existing new energy scheduling research, most of the new energy scheduling research only uses an energy storage battery to store surplus electric quantity, and an effective mode of hydrogen storage is omitted. In the new energy system, the hydrogen production device is added to convert the rich wind and light into green and clean hydrogen energy for long-term storage, only one byproduct of oxygen can be generated in the hydrogen production process, the byproduct can be directly discharged into the atmosphere, the whole reaction can achieve zero pollution, and the hydrogen obtained by hydrogen production can be sold to various hydrogen stations to obtain operation benefits. And a proper amount of energy storage batteries are added into the system to perform power balance adjustment, and the two types of energy storage are controlled in a differentiated mode to realize more operation benefits, so that the economical efficiency of the system operation can be greatly improved while the supply load is ensured. Disclosure of Invention The invention aims to provide an economic dispatching method of a wind-light-hydrogen-storage system aiming at the dispatching problem of a new energy system. The method takes two energy storage modes of a battery and hydrogen production into consideration, stores surplus wind energy and light energy, utilizes the battery to discharge and regulate the balance of power when the load power is insufficient, analyzes the operation characteristics of the hydrogen production device, and realizes the economic dispatch of the system by carrying out coordinated control and optimized solution on the two energy storage modes through dividing the operation interval of the hydrogen production device. The technical scheme of the invention is as follows: an economical dispatching method of a wind-light-hydrogen-storage system comprises the following steps: step one, establishing a new energy system mathematical model comprising a fan, a photovoltaic cell, an energy storage battery and a hydrogen production device, wherein the energy storage battery is selected as a lithium iron phosphate battery, and the hydrogen production device is an alkaline electrolytic tank; step two, providing an objective function comprising system running cost, running income and load electricity shortage punishment, and adding corresponding limiting conditions, wherein the method specifically comprises the following steps: Step 1, obtaining an objective function to be optimized through superposition of system operation cost, operation income and load electricity shortage punishment of T time periods; Step 2, limiting the operating power, the climbing rate and the like of the energy storage battery and the hydrogen production device, and ensuring that each unit can normally operate during scheduling; Analyzing the operation characteristics of the alkaline electrolytic cell, and performing coordinated control on energy storage and the electrolytic cell, wherein the method specifically comprises the following steps: Step