Modeling and multi-objective optimization of integrated MED–TVC desalination system and gas power plant for waste heat harvesting

2021 ◽  
Vol 149 ◽  
pp. 107294
Author(s):  
Hesam Bazargan Harandi ◽  
Anahita Asadi ◽  
Mohammad Rahnama ◽  
Zu-Guo Shen ◽  
Pang-Chieh Sui
Energy ◽  
2018 ◽  
Vol 159 ◽  
pp. 751-765 ◽  
Author(s):  
Kévin Rosset ◽  
Violette Mounier ◽  
Eliott Guenat ◽  
Jürg Schiffmann

2019 ◽  
Vol 137 ◽  
pp. 01001
Author(s):  
Krystian Smolka ◽  
Slawomir Dykas

For many years, the Institute of Power Engineering and Turbomachinery of the Silesian University of Technology has been using a small-capacity (about 500 kWe) steam-gas power plant. Based on many yearsof experience in operation of this power plant utilizing the Velox-type gas-steam system, an idea arose to modify this type of thermal power cycle to create a combined heat and power (CHP) plant of small capacity, dedicated for distributed heat and power production of the range up to 500 kW or production process steam with high temperature. Previous thermodynamic and economic analysis of that type of CHP plant were conducted for natural gas as afuel. The new idea is use the alternative gas fuels or waste heat for Velox-type CHP plant. An adaptation of the Velox-type CHP plant for various fuelscan be done in simple way by moving the combustion chamber out from the setof heat exchangers, in similar way as it is done for HRSG. This paper presents a thermodynamic analysis of the Velox-type steam-gas cycle fired with various alternative gas fuels such as coke gas, blast furnace gas, biogas orgas from gasification. The systems are modelled in the EBSILON® Professional 13 program.


Author(s):  
G. SRINIVAS ◽  
A. K. VERMA ◽  
A. SRIVIDYA ◽  
SANJAY KUMAR KHATTRI

Technical Specifications define the limiting conditions of operation, maintenance and surveillance test requirements for the various Nuclear Power plant systems in order to meet the safety requirements to fulfill regulatory criteria. These specifications impact even the economics of the plant. The regulatory approach addresses only the safety criteria, while the plant operators would like to balance the cost criteria too. The attempt to optimize both the conflicting requirements presents a case to use Multi-objective optimization. Evolutionary algorithms (EAs) mimic natural evolutionary principles to constitute search and optimization procedures. Genetic algorithms are a particular class of EA's that use techniques inspired by evolutionary biology such as inheritance, mutation, natural selection and recombination (or cross-over). In this paper we have used the plant insights obtained through a detailed Probabilistic Safety Assessment with the Genetic Algorithm approach for Multi-objective optimization of Surveillance test intervals. The optimization of Technical Specifications of three front line systems is performed using the Genetic Algorithm Approach. The selection of these systems is based on their importance to the mitigation of possible accident sequences which are significant to potential core damage of the nuclear power plant.


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