研究目的
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.
研究成果
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.
研究不足
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.
1:Experimental Design and Method Selection:
The study employs a novel multi-objective DP method for optimizing the performance of a solar thermal power plant with thermal energy storage. The methodology involves breaking down the complex problem into simpler sub-problems, a characteristic approach of DP.
2:Sample Selection and Data Sources:
The case study is Andasol-I, a grid-connected CSP located in Granada, Spain, with data including solar radiation patterns and technical specifications of the plant.
3:List of Experimental Equipment and Materials:
The plant comprises Solar Field (SF), Thermal Energy Storage (TES) system, and Power Block (PB), with working fluids of heat transfer fluid (HTF), solar salt, and water, respectively.
4:Experimental Procedures and Operational Workflow:
The optimization procedure is carried out for a sample day (21 April 2017) with a specific daily solar pattern. The DP method is applied to determine the optimal charge and discharge management of the TES system.
5:Data Analysis Methods:
The results obtained from the multi-objective DP are compared with those from NSGA-II to verify the superiority of the developed method.
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