Performance enrichment in optimal location and sizing of wind and solar PV centered distributed generation by communal spider optimization algorithm

Abstract

Purpose The distributed generation (DG) proper placement is an extremely rebellious concern for attaining their extreme potential profits. This paper aims to propose the application of the communal spider optimization algorithm (CSOA) to the performance model of the wind turbine unit (WTU) and photovoltaic (PV) array locating method. It also involves the power loss reduction and voltage stability improvement of the ring main distribution system (DS). Design/methodology/approach This paper replicates the efficiency of WTU and PV array enactment models in the placement of DG. The effectiveness of the voltage stability factor considered in computing the voltage stability levels of buses in the DS is studied. Findings The voltage stability levels are augmented, and total losses are diminished for the taken bus system. The accomplished outcomes exposed the number of PV arrays accompanied by the optimal bus location for various penetration situations. Practical implications The optimal placement and sizing of wind- and solar-based DGs are tested on the 15- and 69-test bus system. Originality/value Moreover, the projected CSOA algorithm outperforms the PSOA, IAPSOA, BBO, ACO and BSO optimization techniques.

Quorum sensing centered bacterial horde algorithm for global optimization

“…The current horde optimization methods embrace particle swarm optimization (PSO), [1][2][3][4][5][6] differential evolution, [7][8][9][10] ant cluster optimization (ACO), [11][12][13][14][15][16] simulated bee constellation (SBC), 17,18 biogeography built optimization (BBO), [19][20][21][22][23][24][25][26][27] bat motivated optimization, 28 communal spider optimization, 29,30 multisurrogate assisted metaheuristics optimization, 31 seagull optimization, 32 grasshopper optimization, 33,34 salp swarm optimization, 35,36 levy flight optimization, 37,38 slime mold optimization, 39 sine-cosine optimization, 40 Henry gas solubility optimization, 41 bacterial horde optimization (BHO), 42,43 and so forth applied to real-world practical applications. Some limitations of considered optimization techniques are as follows PSO is computationally economical consequently it expends slight reminiscence and central administering unit speed.…”