Cost Optimization of Steel Beam-to-Column Connections using AVOA

The joint-bolt-African Vulture optimization algorithm(AVOA)model is proposed for the design of building connections to improve the stability of steel beam-to-column connections.For this algorithm,the type of steel is first determined,and the number of bolts needed by the corresponding steel type is referenced in Eurocode 3.Then,the bearing capacity of the joint can be calculated.The joint-bolt-AVOA model is established by substituting the bolt number required by the steel into the algorithm to obtain the optimal bolt number required while ensuring joint stability.The results show that the number of bolts required by the joint-bolt-AVOA model based on the stability of steel is lower than that calculated by Eurocode 3.Therefore,AVOA can effectively optimize the number of bolts needed in building connections and save resources.

Dual degree branched type-2 fuzzy controller optimized with a hybrid algorithm for frequency regulation in a triple-area power system integrated with renewable sources

The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sources such as solar and wind necessitate the use of an efficient load frequency control(LFC)technique.Therefore,a hybrid version of two metaheuristic algorithms(arithmetic optimization and African vulture’s optimization algorithm)is developed.It is called the‘arithmetic optimized African vulture’s optimization algorithm(AOAVOA)’.This algorithm is used to tune a novel type-2 fuzzy-based proportional–derivative branched with dual degree-of-freedom proportional–integral–derivative controller for the LFC of a three-area hybrid deregulated power system.Thermal,electric vehicle(EV),and DRG sources(including a solar panel and a wind turbine system)are con-nected in area-1.Area-2 involves thermal and gas-generating units(GUs),while thermal and geothermal units are linked in area-3.Practical restrictions such as thermo-boiler dynamics,thermal-governor dead-band,and genera-tion rate constraints are also considered.The proposed LFC method is compared to other controllers and optimizers to demonstrate its superiority in rejecting step and random load disturbances.By functioning as energy storage ele-ments,EVs and DRG units can enhance dynamic responses during peak demand.As a result,the effect of the afore-mentioned units on dynamic reactions is also investigated.To validate its effectiveness,the closed-loop system is subjected to robust stability analysis and is compared to various existing control schemes from the literature.It is determined that the suggested AOAVOA improves fitness by 40.20%over the arithmetic optimizer(AO),while fre-quency regulation is improved by 4.55%over an AO-tuned type-2 fuzzy-based branched controller.