Photovoltaic Energy Storage Capacity Optimization Using Genetic Algorithms
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Solution Overview
Problem
The operation efficiency of photovoltaic power stations is reduced due to improper configuration of energy storage capacity, leading to energy wastage and decreased efficiency of hybrid energy storage systems.
Innovation Solution
An optimal configuration method for energy storage capacity using a genetic algorithm, which involves obtaining original output data from photovoltaic power stations, constructing a genetic algorithm model, and performing optimization operations to recommend an optimal energy storage capacity for building energy storage devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If energy storage capacity is increased to improve photovoltaic energy absorption, then the absorptive capacity of wind and light energy is improved, but the initial cost and operating cost of the energy storage device increases
Solution Approach 1:
The patent applies parameter changes by using genetic algorithm to optimize the energy storage capacity parameters. The system dynamically adjusts the energy storage capacity based on photovoltaic output characteristics, grid demand, and economic parameters (initial cost, operating cost, depreciation, interest rate, tax rate) to find the optimal balance between absorption capacity and cost, rather than using fixed or excessive capacity
Solution Approach 2:
The system performs self-service by automatically calculating and determining the optimal energy storage capacity through the genetic algorithm optimization model. The model autonomously evaluates different capacity scenarios considering photovoltaic output data, cost parameters, and operational requirements to identify the optimal configuration without manual intervention
2Quantity of substance
If energy storage capacity is improperly configured to reduce initial cost, then economy is improved, but photovoltaic energy is wasted and operating efficiency is reduced
Solution Approach 1:
The patent applies preliminary action by pre-calculating and determining the optimal energy storage capacity before the photovoltaic power station operates. The genetic algorithm model uses historical photovoltaic output data and operational parameters to predict and establish the optimal capacity configuration in advance, preventing energy wastage from the outset rather than adjusting after problems occur
Solution Approach 2:
The system implements feedback by using the fitness function to continuously evaluate the performance of different energy storage capacity configurations. The optimization model incorporates feedback from photovoltaic output characteristics, grid absorption requirements, and economic parameters to iteratively improve the capacity determination and minimize energy wastage
Data Source
AI summary
An optimal configuration method and device for energy storage capacity of an optical storage system, and apparatus and storage medium are provided, and relates to the photovoltaic field. The specific steps includes: obtaining original output data of a photovoltaic power station for step output; constructing a model of genetic algorithm, and determining algorithm parameters and a fitness function of the genetic algorithm; performing optimization operation based on the genetic algorithm and the original output data to obtain a recommended energy storage capacity, and building an energy storage device according to the recommended energy storage capacity.