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A Novel Multi-objective Dynamic Programming Optimization Method: Performance Management of a Solar Thermal Power Plant as a Case Study

DOI:10.1016/j.energy.2018.11.079 期刊:Energy 出版年份:2018 更新时间:2025-09-23 15:21:21
摘要: Due to the intermittent nature of solar irradiance, solar power plants are usually equipped with energy storage systems. Suitable charge and discharge management of the storage systems can considerably help increase the reliability and profitability of the solar systems. In this regard, various optimization approaches, with their own strengths and limitations, have been employed by literature. Dynamic Programming (DP) is one of the fittest approaches for the wide range of engineering problems which exhibit the properties of overlapping sub-problems. DP is a simple, gradient-free, efficient, and deterministic optimization method that guarantees the optimal solution. However, this method has not been developed for multi-objective problems. This study develops a multi-objective DP method and employs it for the performance management of a solar power plant equipped with thermal energy storage system. “Daily electricity generation” and “daily revenue obtained from selling electricity” are considered to be the objective functions. The superiority of the developed method is shown through a comparison with one of the most commonly used multi-objective optimization approaches, NSGA-II. This comparison indicates that the multi-objective DP attains 3.0%- 7.5% greater values of electricity generation and 3.1%-12.6% higher values of revenue than NSGA-II, for the different levels of solar radiation.
作者: Javad Mahmoudimehr,Parvin Sebghati
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To develop a multi-objective Dynamic Programming (DP) method for the performance management of a solar power plant equipped with a thermal energy storage system, aiming to maximize daily electricity generation and daily revenue from selling electricity.

The developed multi-objective DP method effectively optimizes the performance of a solar thermal power plant with thermal energy storage, achieving higher daily electricity generation and revenue compared to NSGA-II. The method's deterministic nature and simplicity make it a preferable choice for problems with overlapping sub-properties. Future research could extend its application to other engineering problems and compare its performance with additional optimization approaches.

The study is limited to a specific case study (Andasol-I) and a sample day's solar radiation pattern. The applicability of the developed method to other solar power plants or under different operational conditions is not explored. Additionally, the method's effectiveness is compared only against NSGA-II, and its performance relative to other optimization methods is not assessed.

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