Cuckoo Search Case Study
1.8. Cuckoo Search (CS)
Cuckoo Search is a new meta-heuristic algorithm or solving optimization problems is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour of some birds and fruit flies [106]. Nadjemi et al [107] proposed an update literature review on optimization techniques used for the sizing and energy management of HRES. Furthermore, they have proposed a new sizing approach based on cuckoo search (CS) algorithm for grid-connected hybrid energy systems. The sizing optimization is a multi-objective problem with economic, technical and environmental constraints
2. Multi objective design There are two common approaches of multi-objective design. First general …show more content…
A multi-objective probabilistic method to solve the Volt/Var control problem in distribution system with high wind power penetration [28]. A probabilistic load flow approach using Point Estimate Method (PEM) is employed to model the uncertainty in load demands and electrical power generation of WFs. To regard the operational and economic assessment of system containing WFs and FCPPs, different objective functions have been taken into account. Maheri et al. [108] proposed two algorithms for multi objective optimization in wind-PV-diesel generator based system. In one scenario, most reliable system was created under cost constraint and in second scenario, the most cost-effective system was obtained under reliability constraint. Abbes et al. [85]developed 120 Pareto optimal set for PV–wind based integrated system and choose a configuration that fulfills 95% of residential electricity needed. Tant et al. [109]proposed a multi-objective optimization method in SPV with battery energy storage systems and applied the proposed system in the public low-voltage distribution grid. They also presented the isocost trade-off curves between the objectives of peak shaving and voltage control. Moura et al. …show more content…
In iterative approach, optimization model generally considers the LPSP model for power reliability and net present value (NPV), and/or levelised cost of energy (LCE) model for system cost respectively. Most of the authors considered parameters i.e. the capacity of PV panels, rated power of wind system, and battery bank storage capacity. For the desired reliability level, the optimum configuration is one which having the lowest LCE/NPV from all the possible sets of configurations. In this method, system cost is minimized either by linearly changing the values of the parameters or by linear programming techniques. Furthermore, iterative technique does not optimize the PV area, PV module slope angle, wind turbine swept area, wind turbine installation heights as these parameters enormously influenced system costs (LCE and/or
Cuckoo Search is a new meta-heuristic algorithm or solving optimization problems is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour of some birds and fruit flies [106]. Nadjemi et al [107] proposed an update literature review on optimization techniques used for the sizing and energy management of HRES. Furthermore, they have proposed a new sizing approach based on cuckoo search (CS) algorithm for grid-connected hybrid energy systems. The sizing optimization is a multi-objective problem with economic, technical and environmental constraints
2. Multi objective design There are two common approaches of multi-objective design. First general …show more content…
A multi-objective probabilistic method to solve the Volt/Var control problem in distribution system with high wind power penetration [28]. A probabilistic load flow approach using Point Estimate Method (PEM) is employed to model the uncertainty in load demands and electrical power generation of WFs. To regard the operational and economic assessment of system containing WFs and FCPPs, different objective functions have been taken into account. Maheri et al. [108] proposed two algorithms for multi objective optimization in wind-PV-diesel generator based system. In one scenario, most reliable system was created under cost constraint and in second scenario, the most cost-effective system was obtained under reliability constraint. Abbes et al. [85]developed 120 Pareto optimal set for PV–wind based integrated system and choose a configuration that fulfills 95% of residential electricity needed. Tant et al. [109]proposed a multi-objective optimization method in SPV with battery energy storage systems and applied the proposed system in the public low-voltage distribution grid. They also presented the isocost trade-off curves between the objectives of peak shaving and voltage control. Moura et al. …show more content…
In iterative approach, optimization model generally considers the LPSP model for power reliability and net present value (NPV), and/or levelised cost of energy (LCE) model for system cost respectively. Most of the authors considered parameters i.e. the capacity of PV panels, rated power of wind system, and battery bank storage capacity. For the desired reliability level, the optimum configuration is one which having the lowest LCE/NPV from all the possible sets of configurations. In this method, system cost is minimized either by linearly changing the values of the parameters or by linear programming techniques. Furthermore, iterative technique does not optimize the PV area, PV module slope angle, wind turbine swept area, wind turbine installation heights as these parameters enormously influenced system costs (LCE and/or