CN-122009432-A - Double-loop optimization method and system for ship energy storage capacity of hydrogen fuel cell

CN122009432ACN 122009432 ACN122009432 ACN 122009432ACN-122009432-A

Abstract

The invention relates to a hydrogen fuel cell ship energy storage capacity double-loop optimization method and system, which comprises the steps of firstly obtaining a fuel cell system, an energy storage system and hydrogen related parameters, calculating system efficiency and initial investment cost, constructing an inner loop and outer loop cooperative double-layer optimization framework, setting an energy storage system rated capacity search range and generating a candidate solution set, aiming at each candidate solution, extracting charge and discharge loops by adopting a rain flow counting method based on a charge state curve of a ship complete operation cycle, calculating equivalent cycle life, further establishing an objective function comprising hydrogen consumption cost and energy storage loss cost, and iteratively updating the candidate solutions by using a mixed particle swarm gray wolf optimization algorithm by using the minimum total operation cost of the inner loop as feedback until convergence, outputting optimal energy storage capacity and a corresponding power distribution strategy, thereby realizing capacity allocation and energy management cooperative optimization and remarkably reducing the whole life cycle operation cost.

Inventors

WANG HONGXING
CAO MU
LIU WEI
ZHANG YU
Tan Zhaokai
CHEN MINGYU
RUI JIXIANG

Assignees

上海船舶运输科学研究所有限公司

Dates

Publication Date: 20260512
Application Date: 20251210

Claims (10)

1. The double-loop optimization method for the energy storage capacity of the hydrogen fuel cell ship is characterized by comprising the following steps of: S1, acquiring simulation parameters of a fuel cell system, characteristic parameters of an energy storage system and hydrogen parameters in a hydrogen fuel cell ship, wherein the simulation parameters comprise actual output power and output power change rate of the fuel cell system, the characteristic parameters comprise maximum output power, actual state of charge, rated capacity, unit power cost, unit capacity cost and sampling time interval of the energy storage system, the hydrogen parameters comprise hydrogen price, hydrogen low heating value and hydrogen consumption rate, the efficiency of the fuel cell system is calculated according to the actual output power, the hydrogen low heating value and the hydrogen consumption rate of the fuel cell system, and the initial investment cost of the energy storage system is calculated according to the maximum output power, the unit power cost, the unit capacity cost and the rated capacity of the energy storage system; S2, constructing an inner-outer loop cooperative double-layer optimization framework, wherein an outer loop in the double-layer optimization framework sets a search range of rated capacity of an energy storage system, and initializing a plurality of candidate solutions in the search range, wherein each candidate solution represents an additional capacity value of the energy storage system, so as to generate an initial capacity candidate solution set of the energy storage system: S2.1, calculating the current efficiency of the energy storage system according to the actual output power of the energy storage system, calculating the residual energy of the energy storage system based on the current efficiency of the energy storage system, the actual output power of the energy storage system and a sampling time interval, calculating the charge state of the energy storage system at each moment according to the residual energy and rated capacity of the energy storage system, further drawing a charge state change curve of the ship in a complete operation period, wherein the operation period comprises a cruising stage, a port leaning stage, a berthing stage and a starting stage; S2.2, setting up a hydrogen consumption cost model according to the actual output power of the fuel cell system, the hydrogen price, the low heat value of the hydrogen and the efficiency of the fuel cell system under a plurality of constraint conditions established by limiting the output power and the change rate of the output power of the fuel cell system, limiting the output power of the energy storage system, limiting the charge state of the energy storage system and limiting the balance of the total output power, setting up an energy storage system loss cost model according to the service lives of the first group of energy storage system and the second group of energy storage system and the initial investment cost of the energy storage system, setting up an objective function based on the hydrogen consumption cost model and the energy storage system loss cost model, calculating the optimal solution of the objective function by adopting a mixed grain gray wolf optimization algorithm with the current candidate solution as input, and further obtaining an optimal power distribution strategy corresponding to the minimum total operation cost of the ship under the current candidate solution; S2.3, feeding back the current candidate solution and the minimum total running cost of the corresponding ship to the current candidate solution to an outer ring; s3, the outer ring generates a group of new capacity candidate solution sets by utilizing the mixed particle swarm gray wolf optimization algorithm according to the minimum total running cost of the ship corresponding to all the candidate solutions so as to update the capacity candidate solution sets of the energy storage system; And S4, repeatedly executing the steps S2.1 to S2.3 and the step S3 until a preset convergence condition is met, outputting the rated capacity of the energy storage system which minimizes the total running cost of the ship as the optimal rated capacity, and outputting the fuel cell system corresponding to the optimal rated capacity and the optimal power distribution strategy of the energy storage system.
2. The hydrogen fuel cell ship energy storage capacity double-loop optimization method according to claim 1, wherein in the step S2.2, the mixed particle swarm gray wolf optimization algorithm is an optimization algorithm improved on the basis of the particle swarm optimization algorithm and the gray wolf optimization algorithm, and the mixed particle swarm gray wolf optimization algorithm introduces a speed and position update mechanism of the particle swarm optimization algorithm into the gray wolf optimization algorithm when performing inner loop or outer loop optimization, and specifically comprises: a. Each candidate solution is encoded into an individual to form an initial population, and the velocity vector of each individual in the initial population is updated according to the following formula: , Wherein, the A velocity vector for an individual; Is the position vector of the individual, z is the previous iteration number, r 1 、r 2 、r 3 is a random vector between 0 and 1, gamma is the inertial weight, and C 1 、C 2 、C 3 is the acceleration coefficient; b. For each individual, its location vector is updated according to the following formula: , Wherein, the Is the first The position vector of the individual at the z-th iteration, Is the first Velocity vector for each individual at iteration z+1.
3. The hydrogen fuel cell ship energy storage capacity double-loop optimization method according to claim 2, wherein in the process of calculating a distance vector between any common individual and three leader individuals by using the mixed particle swarm gray wolf optimization algorithm, the weights of the three leader individuals in different optimization stages are changed by introducing inertia weight factors, wherein the three leader individuals are respectively the most adaptive, suboptimal and third optimal individuals in a current population, the common individuals are the rest individuals except the three leader individuals in the current population, the fitness of each individual in an initial population is calculated by using an objective function, and the distance vector is calculated according to the following formula: ; ; ; Wherein, the 、、 Distance vectors between the common individual and three leaders respectively; Is an inertial weight factor; 、、 In the form of a vector of acceleration coefficients; α 、 β 、 δ Position vectors of three leader individuals respectively; is the position vector of the common individual.
4. The hydrogen fuel cell ship energy storage capacity double-loop optimization method according to claim 2, wherein the mixed particle swarm gray wolf optimization algorithm replaces a convergence factor decreasing with iteration linearity in the gray wolf optimization algorithm by a nonlinear control strategy, and the nonlinear control strategy is updated according to the following formula: , Wherein, the The method is a nonlinear control strategy, Z is the previous iteration number, and Z is the maximum iteration number.
5. The hydrogen fuel cell vessel energy storage capacity double loop optimization method according to claim 1, wherein in the step S2.2, the plurality of constraints include a first constraint condition and a second constraint condition established with the output power and the output power change rate of the fuel cell system being constrained, a third constraint condition established with the output power of the energy storage system being constrained, a fourth constraint condition established with the state of charge of the energy storage system being constrained, and a fifth constraint condition established with the total output power balance being constrained; the simulation parameters further comprise maximum output power and minimum output power of the fuel cell system, the characteristic parameters further comprise maximum output power, minimum state of charge and maximum state of charge of the energy storage system, the fuel cell system comprises a first group of fuel cell systems and a second group of fuel cell systems, the first constraint condition is constructed according to the actual output power, the maximum output power and the minimum output power of the fuel cell systems, the second constraint condition is constructed according to the change rate of the output power of the fuel cell systems, the current moment and the actual output power of the fuel cell systems at the moment before the current moment, the third constraint condition is constructed according to the actual output power and the maximum output power of the energy storage system, the fourth constraint condition is constructed according to the actual state of charge, the minimum state of charge and the maximum state of charge, and the fifth constraint condition is constructed according to the actual output power of the first group of fuel cell systems, the actual output power of the second group of fuel cell systems, the actual output power of the first group of energy storage systems and the actual output power of the second group of energy storage systems.
6. The hydrogen fuel cell ship energy storage capacity double-loop optimization method according to claim 1, wherein in the optimal power distribution strategy obtained in the step S2.2, in a starting stage that load power reaches a peak value in a ship operation process, the first group of energy storage systems are powered by maximum output power, the second group of energy storage systems are used as auxiliary power sources to be put into operation, and the first group of energy storage systems are cooperated to meet the requirement of peak load power.
7. The hydrogen fuel cell ship energy storage capacity double-loop optimization system is characterized by comprising a parameter acquisition and calculation module, a double-loop iteration optimization module, an outer loop updating module and a loop convergence judgment module which are connected in sequence, wherein the double-loop iteration optimization module comprises an outer loop initialization sub-module and an inner loop optimization sub-module, and the inner loop optimization sub-module comprises a service life calculation unit, a cost and power allocation strategy calculation unit and a feedback unit; The parameter acquisition and calculation module acquires simulation parameters of a fuel cell system in a hydrogen fuel cell ship, characteristic parameters of an energy storage system and hydrogen parameters, wherein the simulation parameters comprise actual output power and output power change rate of the fuel cell system, the characteristic parameters comprise maximum output power, actual state of charge, rated capacity, unit power cost, unit capacity cost and sampling time interval of the energy storage system, the hydrogen parameters comprise hydrogen price, hydrogen low heat value and hydrogen consumption rate, the efficiency of the fuel cell system is calculated according to the actual output power, the hydrogen low heat value and the hydrogen consumption rate of the fuel cell system, and the initial investment cost of the energy storage system is calculated according to the maximum output power, the unit power cost, the unit capacity cost and the rated capacity cost of the energy storage system; the outer ring initialization submodule constructs a double-layer optimization framework with cooperative inner and outer rings, wherein the outer ring in the double-layer optimization framework sets a search range of rated capacity of the energy storage system, initializes a plurality of candidate solutions in the search range, and each candidate solution represents a rated capacity value of the energy storage system so as to generate an initial candidate solution set of the capacity of the energy storage system; The inner loop optimization sub-module performs, for each candidate solution in the set of capacity candidate solutions, an optimization process of an inner loop in the following two-layer optimization architecture by an internal unit: The service life calculation unit calculates the current efficiency of the energy storage system according to the actual output power of the energy storage system, calculates the residual energy of the energy storage system based on the current efficiency of the energy storage system, the actual output power of the energy storage system and a sampling time interval, calculates the charge state of the energy storage system at each moment according to the residual energy and the rated capacity of the energy storage system, further draws a charge state change curve of the ship in a complete operation period, wherein the operation period comprises a cruising stage, a port leaning stage, a berthing stage and a starting stage; The cost and power distribution strategy calculation unit is used for establishing a hydrogen consumption cost model according to the actual output power of the fuel cell system, the hydrogen price, the hydrogen low heat value and the efficiency of the fuel cell system under a plurality of constraint conditions established by taking the output power and the output power change rate limit of the fuel cell system, the output power limit of the energy storage system, the state of charge limit of the energy storage system and the total output power balance limit as constraints, establishing an energy storage system loss cost model according to the service lives of the first group of energy storage systems and the second group of energy storage systems and the initial investment cost of the energy storage systems, and constructing an objective function based on the hydrogen consumption cost model and the energy storage system loss cost model; The feedback unit feeds back the current candidate solution and the minimum total running cost of the corresponding ship to the outer ring; The outer ring updating module is used for generating a new capacity candidate solution set by utilizing the mixed particle swarm gray wolf optimization algorithm according to the minimum total running cost of the ship corresponding to all the candidate solutions so as to update the capacity candidate solution set of the energy storage system; and the cyclic convergence judging module repeatedly executes the inner ring optimizing sub-module to the outer ring updating module until a preset convergence condition is met, outputs the rated capacity of the energy storage system which minimizes the total running cost of the ship as the optimal rated capacity, and outputs the optimal power distribution strategy of the fuel cell system and the energy storage system corresponding to the optimal rated capacity.
8. The hydrogen fuel cell vessel energy storage capacity double loop optimization system of claim 7, wherein in the cost and power distribution strategy calculation unit, the plurality of constraints include a first constraint and a second constraint established with the output power and the rate of change of the output power of the fuel cell system being limited as constraints, a third constraint established with the output power of the energy storage system being limited as constraints, a fourth constraint established with the state of charge of the energy storage system being limited as constraints, and a fifth constraint established with the total output power balance constraint being limited as constraints.
9. The hydrogen fuel cell vessel energy storage capacity double loop optimization system of claim 8, wherein the simulation parameters further comprise maximum output power and minimum output power of the fuel cell system, the characteristic parameters further comprise maximum output power, minimum state of charge and maximum state of charge of the energy storage system, the fuel cell system comprises a first group of fuel cell systems and a second group of fuel cell systems, the first constraint is constructed according to the actual output power, the maximum output power and the minimum output power of the fuel cell systems, the second constraint is constructed according to the change rate of the output power of the fuel cell systems, the current moment and the output power of the fuel cell systems at the moment before the current moment, the third constraint is constructed according to the actual output power and the maximum output power of the energy storage system, the fourth constraint is constructed according to the actual state of charge, the minimum state of charge and the maximum state of charge of the energy storage system, and the fifth constraint is constructed according to the actual output power of the first group of fuel cell systems, the actual output power of the second group of fuel cell systems, the actual output power of the first group of energy storage systems, and the actual output power of the second group of energy storage systems.
10. The hydrogen fuel cell ship energy storage capacity double-loop optimization system according to claim 7, wherein in the optimal power distribution strategy obtained by the cost and power distribution strategy calculation unit, in a departure stage that load power reaches a peak value in a ship operation process, the first group of energy storage systems are powered by maximum output power, and the second group of energy storage systems serve as auxiliary power sources to be put into operation, and the first group of energy storage systems are cooperated to meet the requirement of peak load power.

Description

Double-loop optimization method and system for ship energy storage capacity of hydrogen fuel cell Technical Field The invention relates to the technical field of ship hybrid energy, in particular to a hydrogen fuel cell ship energy storage capacity double-loop optimization method and system. Background With the increasing prominence of greenhouse gas emissions in the shipping industry, hydrogen fuel cells are gaining wide attention as a low emission power source in marine electric propulsion systems. Because the hydrogen fuel cell has inherent defects of slow cold start and delayed dynamic response, the load fluctuation requirements of the ship under complex working conditions such as cruising, port leaning, starting and the like cannot be met independently, and the ship usually adopts a mixed energy system consisting of the fuel cell and energy storage equipment to meet the power requirements of the ship. The reasonable configuration of the capacity of the energy storage system is closely related to the energy management problem, and the operation efficiency, stability and economy of the hybrid energy system are directly affected. The existing energy storage system capacity optimization method mainly can be divided into decoupling and coupling. The decoupling method solves the capacity configuration and the energy management problem independently, has simple flow, but is difficult to obtain global optimal solution, and the coupling method synchronously processes the two problems through multi-objective optimization, but the weight coefficient in the objective function is determined empirically, so that the objectivity and the accuracy of the optimization result are affected. In addition, when the existing common optimization algorithms, such as Particle Swarm (PSO) algorithm and Gray Wolf (GWO) algorithm, are used for solving the complex optimization problems of high dimension, nonlinearity and multiple constraints, the problems of easy local optimization, slow convergence speed and the like generally exist, so that the optimization effect is poor, and the cooperative requirements of the optimization precision and the efficiency under the complex working condition of the ship are difficult to meet. In order to solve the above problems, a new method for optimizing the capacity of the energy storage system, which can achieve both optimization accuracy and solution efficiency and consider the influence of multi-factor coupling, is needed to achieve significant reduction of the optimal capacity of the energy storage system and the running cost of the ship. Disclosure of Invention The invention provides a double-loop optimization method for the energy storage capacity of a hydrogen fuel cell ship, which can realize collaborative optimization of the rated capacity and the power distribution strategy of the energy storage system, accurate modeling of the cycle life of the battery and comprehensive minimization of the running cost of the whole life cycle, and obviously improve the overall search efficiency and solving precision, and aims to solve the problems that the current hydrogen fuel cell ship is single in optimization target, dependent on experience of capacity design, difficult to cooperate with running cost and service life loss, low in convergence speed of a traditional optimization algorithm, easy to fall into local optimization and the like in the energy storage system configuration and energy management process. The invention also relates to a hydrogen fuel cell ship energy storage capacity double-loop optimization system. The technical scheme of the invention is as follows: The double-loop optimization method for the energy storage capacity of the hydrogen fuel cell ship is characterized by comprising the following steps of: S1, acquiring simulation parameters of a fuel cell system, characteristic parameters of an energy storage system and hydrogen parameters in a hydrogen fuel cell ship, wherein the simulation parameters comprise actual output power and output power change rate of the fuel cell system, the characteristic parameters comprise maximum output power, actual state of charge, rated capacity, unit power cost, unit capacity cost and sampling time interval of the energy storage system, the hydrogen parameters comprise hydrogen price, hydrogen low heating value and hydrogen consumption rate, the efficiency of the fuel cell system is calculated according to the actual output power, the hydrogen low heating value and the hydrogen consumption rate of the fuel cell system, and the initial investment cost of the energy storage system is calculated according to the maximum output power, the unit power cost, the unit capacity cost and the rated capacity of the energy storage system; S2, constructing an inner-outer loop cooperative double-layer optimization framework, wherein an outer loop in the double-layer optimization framework sets a search range of rated capacity of an energy storage system, and