Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm

Energy ◽  
2019 ◽  
Vol 171 ◽  
pp. 256-269 ◽  
Author(s):  
Ehab E. Elattar
Author(s):  
Mehrdad Tarafdar Hagh ◽  
Saeed Pouyafar ◽  
Farnaz Sohrabi ◽  
Ayda Shaker ◽  
Morteza Vahid-Ghavidel ◽  
...  

Author(s):  
Roger H Bezdek ◽  

This paper assesses the relative economic and jobs benefits of retrofitting an 847 MW USA coal power plant with carbon capture, utilization, and storage (CCUS) technology compared to replacing the plant with renewable (RE) energy and battery storage. The research had two major objectives: 1) Estimate the relative environmental, economic, and jobs impacts of CCUS retrofit of the coal plant compared to its replacement by the RE scenario; 2) develop metrics that can be used to compare the jobs impacts of coal fueled power plants to those of renewable energy. The hypotheses tested are: 1) The RE option will reduce CO2 emissions more than the CCUS option. We reject this hypothesis: We found that the CCUS option will reduce CO2 emissions more than the RE option. 2) The RE option will generate greater economic benefits than the CCUS option. We reject this hypothesis: We found that the CCUS option will create greater economic and jobs benefits than the RE option. 3) The RE option will create more jobs per MW than the CCUS option. We reject this hypothesis: We found that the CCUS option will create more jobs per MW more than the RE option. We discuss the implications of these findings.


2020 ◽  
Author(s):  
João Pedro Augusto Costa ◽  
Omar Andres Carmona Cortes ◽  
Osvaldo Ronald Saavedra

This paper aims to compare two different parallel approaches (cooperative and competitive) of the SPEA2 for solving the environmental-economic dispatch problem. The idea is to solve the problem by executing the SPEA2 algorithm along with three different meta-heuristics (Genetic Algorithms, Particle Swarm Optimization, and Differential Evolution) to perform changes in the population. The different meta-heuristics work in parallel using two different approaches. The first one is the competitive approach, in which meta-heuristics compete for producing the best set of candidate solutions for solving the problem. Whereas, the cooperative approach selects the new population merging all individuals from all meta-heuristics, then selecting the solution set for the Pareto frontier. The proposal was implemented in C++ using MPI in a master-slave parallel model. Two  study cases were used: the first one with six generators and the second one with forty generators. Results showed that the cooperative approach presented the best Pareto frontier for the case of 40 generators.


2012 ◽  
Vol 12 (11) ◽  
pp. 3500-3513 ◽  
Author(s):  
Nicole Pandit ◽  
Anshul Tripathi ◽  
Shashikala Tapaswi ◽  
Manjaree Pandit

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