Synergistic Application of Particle Swarm Optimization and Gravitational Search Algorithm for Solar PV Performance Improvement

This study aims to optimize photovoltaic systems by developing a novel hybrid metaheuristic approach for maximum power point tracking (MPPT). The proposed method eclectically combines particle swarm optimization (PSO) and gravitational search algorithm (GSA) to overcome individual limitations and leverage complementary strengths. PSO, while surpassing in exploration, may suffer from premature convergence. GSA demonstrates strong exploitation capabilities but can struggle with slow convergence. A simulation model is developed to evaluate the hybrid algorithm’s performance in optimizing PV systems’ duty cycle. The approach utilizes the exploitation capabilities of PSO and GSA to navigate the search space effectively. Results demonstrate that the hybrid algorithm outperforms traditional techniques and standalone metaheuristics, achieving improved convergence time, faster settling time, and enhanced MPPT tracking efficiency. Under varying irradiance conditions, the proposed method consistently delivers higher power generation and improved overall PV system efficiency, offering a promising solution for optimizing PV systems and maximizing energy generation

Transmission Wheeling Pricing in Embedded Cost Using Modified Amp-Mile and MVA Utility Factor Methods

Transmission wheeling pricing is one of the decisive aspects of present open access electricity market. Various methods are available for transmission; however, no method is proved to diverse operating conditions of power system. These methods are not able to quantify the full recovery of embedded cost. All the variables i.e. remaining charges, used circuit capacity are not counted in the existing methods. This Paper explicates two methods, Modified Amp – Mile method and MVA Utility Factor method, to recover embedded cost. Modified Amp-Mile method is customized form of existing Amp-Mile method. In the MVA Utility Factor method, cost allocation is based on marginal participation (MP). It evaluates the cost, using sensitivity analysis of network power. The proposed methods are tested on an IEEE 6 bus system and further verified on Hadoti region real 37 bus system. All the results are presented in Full Recovery Model (FRM) and Partial Recovery Model (PRM)

Decentralized Autonomous Hybrid Renewable Power Generation

Power extension of grid to isolated regions is associated with technical and economical issues. It has encouraged exploration and exploitation of decentralized power generation using renewable energy sources (RES). RES based power generation involves uncertain availability of power source round the clock. This problem has been overcome to certain extent by installing appropriate integrated energy storage unit (ESU). This paper presents technical review of hybrid wind and photovoltaic (PV) generation in standalone mode. Associated components like converters, storage unit, controllers, and optimization techniques affect overall generation. Wind and PV energy are readily available, omnipresent, and expected to contribute major future energy market. It can serve to overcome global warming problem arising due to emissions in fossil fuel based thermal generation units. This paper includes the study of progressive development of standalone renewable generation units based on wind and PV microgrids