CN-115378022-B - Optical storage and filling system design and operation integrated optimization method based on accurate model

CN115378022BCN 115378022 BCN115378022 BCN 115378022BCN-115378022-B

Abstract

The invention relates to an integrated optimization method for the design and operation of an optical storage and filling system based on an accurate model, which comprises the following steps of constructing an accurate prediction model of photovoltaic output power, considering an ordered charging strategy of an electric automobile in constraint conditions, constructing an integrated optimization model for the design and operation of the optical storage and filling system with the system net present value maximized as an optimization target in the whole life cycle of the optical storage and filling system based on the accurate prediction model of the photovoltaic output power, and solving the integrated optimization model to obtain an optimal design scheme and operation strategy. Compared with the prior art, the method has the advantages of high model precision, low model complexity, high feasibility of an optimization scheme, good economy and the like.

Inventors

DONG XIAOJIAN
SHEN JIANI
HE YIJUN

Assignees

上海交通大学

Dates

Publication Date: 20260505
Application Date: 20211104

Claims (8)

1. The integrated optimization method for the design and operation of the optical storage and filling system based on the accurate model is characterized by comprising the following steps of: building a photovoltaic output power accurate prediction model; taking an ordered charging strategy of the electric automobile into consideration in constraint conditions, and constructing an integrated optimization model of the design and operation of the optical storage and charging system by maximizing a system net present value in the whole life cycle of the optical storage and charging system based on the accurate prediction model of the photovoltaic output power; solving the integrated optimization model to obtain an optimal design scheme and an optimal operation strategy; The photovoltaic output power accurate prediction model is based on a single diode R P model, and circuit parameters in the single diode R P model are corrected through a battery photovoltaic mechanism, a radial basis neural network model and weather condition historical data; the constraint conditions comprise power balance constraint, ordered charging constraint, design constraint and operation constraint; The ordered charging constraint is constructed based on random simulation of electric vehicle charging characteristic distribution historical data and electric vehicle/charging pile behavior characteristics, specifically, the random simulation of the electric vehicle/charging pile behavior characteristics is implemented based on the electric vehicle charging characteristic distribution historical data, electric vehicle charging power characteristic data are generated, and electric vehicles and charging piles are matched to obtain arrival/departure time, charging quantity and corresponding charging pile number of each electric vehicle arriving at the optical storage and charging system, and the ordered charging constraint is constructed for subsequent ordered charging constraint.
2. The integrated optimization method for designing and operating a light storage and charging system based on an accurate model according to claim 1, wherein the accurate prediction model of the photovoltaic output power is expressed as: In the formula, The photovoltaic system output power is output power of a photovoltaic system, I and V are current and voltage of the photovoltaic cell respectively, I PV 、I S 、R S 、R P and a are photo-generated current, reverse saturation current, series internal resistance, shunt internal resistance and ideal factors of the photovoltaic cell respectively, correction is achieved based on a photovoltaic mechanism of the photovoltaic cell, a radial basis neural network model and weather condition historical data, T c is cell temperature of the photovoltaic cell, k B is Boltzmann constant, and q is electron volt constant.
3. The integrated optimization method for design and operation of a precision model-based optical storage and filling system according to claim 1, wherein the weather condition history data comprises an environmental temperature, an illumination radiation intensity and a wind speed per hour in one year.
4. The integrated optimization method for designing and operating an optical storage and filling system based on an accurate model according to claim 1, wherein the calculation formula of the net present value of the system is: NPV is the net present value of the system, AOP and TCI represent annual operating profits and total construction investment, respectively, for the system, and CRF l,i is the capital recovery factor for a system lifecycle of i years, the discount rate i.
5. The precision model-based integrated optimization method for optical storage and delivery system design and operation of claim 1, wherein the ordered charge constraint expression comprises: In the formula, To charge the electric car at time t, For the output power of the c-th charging pile at the moment t, deltat is the step length of the system operation optimization, 、 And The arrival time, the departure time and the charge quantity of the v electric automobile corresponding to the c-th charging pile are respectively represented by P pile,min and P pile,max , which are respectively the minimum and maximum output power of the charging pile, and z c,t is a 0-1 variable for judging whether the charging pile c is idle at the t time.
6. The integrated optimization method for the design and operation of an optical storage and charging system based on the accurate model according to claim 1, wherein the electric vehicle charging characteristic distribution history data includes time-sharing time interval distribution of electric vehicles reaching charging stations, charge amount demand distribution and additional residence time distribution at the charging stations.
7. The integrated optimization method for designing and operating an optical storage and filling system based on an accurate model according to claim 1, wherein the implementation step of random simulation of the behavior characteristics of the electric vehicle/the charging pile comprises the following steps: According to the electric vehicle charging characteristic distribution history data, the distribution characteristics of an electric vehicle arrival time interval delta t car , an additional stay time delta t extra and a charging electric quantity demand e pile are constructed; generating a large amount of characteristic data of the characteristic parameters based on a Monte Carlo simulation method; and calculating key factors of the charging behavior of the electric automobile to construct the ordered charging constraint.
8. The integrated optimization method for designing and operating an optical storage and filling system based on an accurate model according to claim 1, wherein the constraint condition is a linear constraint condition subjected to linearization.

Description

Optical storage and filling system design and operation integrated optimization method based on accurate model Technical Field The invention relates to the field of comprehensive energy system design optimization, in particular to an integrated optimization method for the design and operation of an optical storage and filling system based on an accurate model. Background In smart power grid construction, realize the organic integration of electric automobile and renewable energy, there is the promotion effect to the application of both, help improving the economic and environmental benefit of whole operation. The photovoltaic-energy storage-charging pile system (optical storage and charging system) is a micro-grid system with wide application prospect. The optical storage and charging system can effectively improve the resource utilization rate of solar energy, relieve the pressure of a main power grid, reduce carbon emission and improve the economic benefit of the system. With the popularization of photovoltaic system low-price internet surfing and the rapid development of electric automobile industry, the optical storage and charging system has wide application prospect, and a large number of demonstration projects and commercial application projects based on the optical storage and charging system are also built and applied in various places around the world. The implementation of the design and operation optimization of the optical storage and filling system has important significance for improving the renewable energy consumption efficiency and the overall economy of the optical storage and filling system and realizing the rapid popularization and application under different source-load characteristic scenes. Because of strong coupling between the design and the operation process of the optical storage and filling system, in the stage of system design, historical source-load characteristic data are generally required to be combined, and meanwhile, the operation strategy is optimized, so that a feasible optimal design scheme is expected to be obtained. Therefore, the design and operation integrated optimization of the optical storage and filling system is receiving more and more attention, but the implementation of the optical storage and filling system still has great challenges due to the difficulty in guaranteeing the reliability of the optimization result. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide the integrated optimization method for the design and operation of the optical storage and filling system based on the accurate model, which has the advantages of high model precision, low model complexity, high feasibility of an optimization scheme and good economy. The aim of the invention can be achieved by the following technical scheme: An integrated optimization method for the design and operation of an optical storage and filling system based on an accurate model comprises the following steps: building a photovoltaic output power accurate prediction model; taking an ordered charging strategy of the electric automobile into consideration in constraint conditions, and constructing an integrated optimization model of the design and operation of the optical storage and charging system by maximizing a system net present value in the whole life cycle of the optical storage and charging system based on the accurate prediction model of the photovoltaic output power; And solving the integrated optimization model to obtain an optimal design scheme and an optimal operation strategy. Further, the photovoltaic output power accurate prediction model is based on a single diode R P model, and circuit parameters in the single diode R P model are corrected through a battery photovoltaic mechanism, a radial basis function neural network model and weather condition historical data. Further, the photovoltaic output power accurate prediction model is expressed as: In the formula, The photovoltaic system output power is output power of a photovoltaic system, I and V are current and voltage of the photovoltaic cell respectively, I PV、IS、RS、RP and a are photo-generated current, reverse saturation current, series internal resistance, shunt internal resistance and ideal factors of the photovoltaic cell respectively, correction is achieved based on a photovoltaic mechanism of the photovoltaic cell, a radial basis neural network model and weather condition historical data, T c is cell temperature of the photovoltaic cell, k B is Boltzmann constant, and q is electron volt constant. Further, the weather condition history data includes ambient temperature, illumination radiation intensity, and wind speed per hour over a year. Further, the calculation formula of the system net present value is as follows: NPV is the net present value of the system, AOP and TCI represent annual operating profits and total construction investment, respectively, for the system, and CRF l,i is the c