Solve environmental economic dispatch of Smart MicroGrid containing distributed generation system – Using chaotic quantum genetic algorithm
By Gwo-Ching Liao. 2012
152 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/4bfd8af87a0a6aa48e08e1a2f2faf657aa8b71cf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Oliver Sawodny
- Julia Sachs
- Luigi Glielmo
- Alessandra Parisio
- Nima Nikmehr
- Sajad Najafi Ravadanegh
- Evangelos Rikos
In Electrical and Electronic Engineering
- Oliver Sawodny
- Julia Sachs
- Luigi Glielmo
- Alessandra Parisio
- Nima Nikmehr
- Sajad Najafi Ravadanegh
- Evangelos Rikos
Citations in the corpus
- Optimal Power Dispatch of Multi-Microgrids at Future Smart Distribution Grids (2015, methodology): “tum genetic algorithm [17], [18], ant colony [19], differential evolution algorithm [20], Tabu search, genetic algorithm [21], and niching evolutionary algorithm [22] are methods that used”
- A Model Predictive Control Approach to Microgrid Operation Optimization (2014, methodology): “Metaheuristics and heuristics have been proposed to solve the power dispatch problem for microgrids, such as genetic algorithms [12], evolutionary strategies, and tabu search algorithms [13].”
- A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural Areas (2016, methodology): “Other methods, applied for the determination of the optimal energy dispatch, are meta-heuristic and heuristic optimization approaches such as the chaotic quantum genetic algorithm [6], the multi-period gravitational search [7] or a self adaptive optimization algorithm based on q-particle swarm optim”