This study proposes the application of an efficient and hybrid meta-heuristic algorithm of Harris Hawk-Particle Swarm Optimizer (HHOPSO) for solving voltage constrained reactive power planning (VCR...

Voltage Constrained Reactive Power Planning Problem for Reactive Loading Variation Using Hybrid Harris Hawk Particle Swarm Optimizer

Performance optimization of annealing salp swarm algorithm: frameworks and applications for engineering design

OUP accepted manuscript

Salp Swarm Algorithm (SSA) is a novel optimization algorithm which is widely used in engineering problems An improved SSA inspired by quantum computing is proposed in this paper The principles of quantum computing, such as qubits and quantum states, are introduced into the original SSA in order to overcome the defect of trapping into local optimum easily Instead of updating the salp position directly, the quantum angle related to the quantum state is updated to increase the diversity of states Two multidimensional benchmark functions are used to verify the proposed improved SSA, the result shows that the introduction of quantum computing can successfully prevent the SSA from falling into the local optimum and increase the accuracy

https://iopscience.iop.org/article/10.1088/1742-6596/1570/1/012016/pdf

An improved salp optimization algorithm inspired by quantum computing

Techno-Economic Model for Reactive Power Planning Using Series-Shunt Compensation Devices Under Load Demand in Power Transmission Network

Optimal reactive power planning is an important task for experts and industrials to ensure the reliability of modern power systems. Actually, the structure of practical power systems becomes dynamic and characterised by uncertainty in load and non-linear characteristic of various elements of power systems such as constraints associated to thermal units, constraints associated with FACTS devices and renewable sources. This study introduces an intelligent strategy based new metaheuristic named Salp swarm algorithm (SSA) to improve the solution of reactive power dispatch by optimising the total power loss, the total voltage deviation individually and simultaneously considering static VAR compensators (SVCs). To improve the efficiency of the original algorithm in solving large test systems, a sub SSA is formed to optimise the various objective functions based on a grouped control variable. In this study, four grouped swarms named SSA_PG for active power, SSA_VG for voltages, SSA_Ti for Tap transformers, and SSA_SVC for SVCs are formed to operate in a flexible structure to minimise a specified objective function. The proposed intelligent planning strategy validated on the IEEE 30 bus and to the large electrical test system 114 Bus of the Algerian network at normal condition and considering critical situations such as margin loading stability and contingency. Results found using the proposed strategy compared to those cited recently in the literature proves its particularity in terms of solution quality and convergence characteristics.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2018.5772

New strategy based modified Salp swarm algorithm for optimal reactive power planning: a case study of the Algerian electrical system (114 bus)

With industry development, suburbanization, and population growth, the load demand is constantly increasing year by year. Excessive load demand has greatly strained the distribution network (DN), resulting in increased power losses due to the high-power flow. Therefore, it becomes very important to minimize power losses at the DN to maximize the efficiency of the distribution companies. Network reconfiguration is one of the effective methods used by distribution companies to minimize losses in the DN. This paper proposes Mayfly Algorithm (MA) to solve network reconfiguration problems and minimize the DN's power loss. MA is inspired by the social behavior of the mayflies, especially their mating process. IEEE-33 bus DN has been used to demonstrate the effectiveness of the proposed method. The obtained simulation results compared with other methods in the literature and comparison showed that the proposed MA provides better quality solutions than other methods. 

Srairi Kamel

Papers

New strategy based modified Salp swarm algorithm for optimal reactive power planning: a case study of the Algerian electrical system (114 bus)

Optimal radial distribution network reconfiguration to minimize power loss by using mayfly algorithm