A hybrid approach based on GA and direct search for periodic optimization of finely distributed storage

Joint Model Predictive Control of Electric and Heating Resources in a Smart Building

“…When the optimization problem is too complex to be solved leveraging standard methods, techniques such as genetic algorithms [29], particle swarm optimization [30] and metaheuristic tabu search [31] are used. Other approaches that can be found applied in this research area are the Lagrangian relaxation [32] and Benders decomposition [33].…”

Economic Model Predictive and Feedback Control of a Smart Grid Prosumer Node

“…Genetic algorithms can be used when large mathematical formulations requiring large computational effort to reach the optimal solution are used [35,36]. For example, in [36] the authors discuss how a local EMS can be designed to optimize the size and operation of an ESS, minimizing the effect of aging and replacement costs. Other heuristic techniques proposed are for example particle swarm optimization [37] and metaheuristic Tabu search [38].…”

Review of residential PV-storage architectures

“…Multiple optimization techniques [47] have been reported, for instance: multi-stage stochastic optimization [48], Lyapunov approach [49], particle swarm based, and fuzzy logic [50]. Additionally, to optimize the cyclic operation of battery, genetic algorithms have been presented in [51]. Another example is the use of a mixed integer programing optimization [52] to minimize the running cost of the system.…”