A novel multi-objective Dynamic Programming optimization method: Performance management of a solar thermal power plant as a case study. (1st February 2019)

• Record Type: Journal Article
• Authors: Mahmoudimehr, Javad; Sebghati, Parvin
• Is Part Of: Energy. Volume 168(2019)
• Page Start: 796
• Page End: 814
• Publication Date: 2019-02-01
• Subjects: Solar thermal power plant -- Thermal energy storage system -- Multi-objective Dynamic Programming method -- Optimal performance; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.11.079
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: 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. Highlights: Development of a multi-objective Dynamic Programming optimization method. Application of the developed method to a solar power plant with storage system. Verification of the developed optimization method through comparison with NSGA-II. Analysis of the influence of objective function on the optimal performance scenario.