Control-Based Maximum Power Point Tracking for a Grid-Connected Hybrid Renewable Energy System Optimized by Particle Swarm Optimization

Author(s):  
Mouna Ben Smida ◽  
Anis Sakly ◽  
Sundarapandian Vaidyanathan ◽  
Ahmad Taher Azar

There has been a great deal of interest in renewable energy sources for electricity generation, particularly for photovoltaic and wind generators. These energy resources have enormous potential and can meet the current global demand for energy. Despite the obvious advantages of renewable energy sources, they have significant disadvantages, such as the discontinuity of their generation, due to their heavy dependence on weather and climate change, which affects their effectiveness in the conversion of renewable energy. Faced with this conflict, it is essential to optimize the performance of renewable systems in order to increase their efficiency. Several unconventional approaches to optimization have been developed in the literature. In this chapter, the management of a hybrid renewable energy system is optimized by intelligent approach based on particle swarm optimization comprising a shaded photovoltaic generator and a wind generator.

Author(s):  
Mouna Ben Smida ◽  
Anis Sakly ◽  
Sundarapandian Vaidyanathan ◽  
Ahmad Taher Azar

There has been a great deal of interest in renewable energy sources for electricity generation, particularly for photovoltaic and wind generators. These energy resources have enormous potential and can meet the current global demand for energy. Despite the obvious advantages of renewable energy sources, they have significant disadvantages, such as the discontinuity of their generation, due to their heavy dependence on weather and climate change, which affects their effectiveness in the conversion of renewable energy. Faced with this conflict, it is essential to optimize the performance of renewable systems in order to increase their efficiency. Several unconventional approaches to optimization have been developed in the literature. In this chapter, the management of a hybrid renewable energy system is optimized by intelligent approach based on particle swarm optimization comprising a shaded photovoltaic generator and a wind generator.


2015 ◽  
Vol 91 ◽  
pp. 83-92 ◽  
Author(s):  
Pablo García-Triviño ◽  
Antonio José Gil-Mena ◽  
Francisco Llorens-Iborra ◽  
Carlos Andrés García-Vázquez ◽  
Luis M. Fernández-Ramírez ◽  
...  

Author(s):  
Pottipati Sai Gangadhar

Abstract: An ordinary PID system and an anti PID saturation technique are used to confirm the dominance of the proposed approach in a wind structure with exchange work. 6. The simulation is performed in MATLAB to designate the predominance of the anticipated calculation. The replica mould is shown in the image. Figure 9 depicts the controller surface waveforms in relation to the planned computation, where the level directions are instance t and the upward arrangements in are input esteem. In the end, the proposed method is capable of deciphering a symphonic disguise. There is a 0.9993-second lag between the factor power and 1, which means the factor power is very close to 1. New power-electronic devices, dubbed "Specific Power Devices," are being developed to reduce power quality problems and provide customers with tailored solutions. Modern s0lutions f0r l0adrelated issues and supply v0ltage flaws are included in UPQC, which stands for Unified Power Quality Conditioners. Shunt Compensation and Series Compensation work together to solve many power quality issues. The series compensator's current and voltage profiles are improved thanks to the shunt compensator. Custom feeding systems have emerged as a result of the assumption that a healthy feeder next to it can compensate for issues in the current feeding unit. With these devices, you'll get better performance than with a unique power supply for each feeder. These unique power devices include the IDVR, IVOLCON, and IUPQC with two voltage stabilisation capacitors, as well as the Interline Dynamic Voltage Restored (IDVR). The use of a new IUPQC topology that concurrently compensates for voltage and current impurities while also improving Power Quality Quality. In typical approaches, f0ur v0ltage source c0nverters (VSC) with multi-tier topologies are taken into account, and a hexagonal coordinate system space vect0r pulse width m0dulation is employed. The PI controller improves power quality while reducing status errors. Because of these drawbacks, the PI controller isn't the best choice for high-reliability applications. Particle Swarm Optimization uses the PI controller installation to further increase power quality (PSO). The IUPQC with Particle Swarm Optimization (PSO) stabilises voltage and current discrepancies for improved power quality in the multibus/multi-feeder system. In order to compensate for voltage changes, a proposed controller utilises a shared capacitor to distribute voltage from healthy feeds to neighbouring feeders. Tw0 feeders with a hybrid renewable energy system implement the researchers' technique. MATLAB/SIMLUNIK was used to analyse IUPQC's results. Keywords: Grid Integrati0n, Multi-Feeder Systems, Multi-Level C0nverters, P0wer Quality Impr0vement, Renewable Energy Systems


Taking into consideration of continuously increasing consumption of the electricity and perturb towards environmental issues, renewable energy sources have been broadly used for generation of electricity. A Hybrid Energy System can be elucidated as systems which consist of various energy sources such as wind, solar, fuel cell, diesel generator and storage systems such as batteries to store energy are integrated and interconnected to satisfy the load energy demand. This paper infers the generation of electricity by utilizing the Hybrid Renewable Energy System (HRES). This paper presents the modelling and future challenges of the HRES.


Author(s):  
Sweta Kumari ◽  
Umesh Kumar Sinha ◽  
Manish Kumar ◽  
Sunil Kumar Jangir ◽  
Ajay Kumar Singh

Aims & Objective: The fast depletion of fossil fuels and the growing awareness of environmental protection has become a concerning topic. Because of this fact, the researchers are working for a long time to generate electrical energy sources due to the intermittent nature of unconventional energy sources such as solar, wind geothermal, tidal, and biomass as a sustainable, cost-effective, and environmentally friendly alternative for conventional energy sources. These systems are interconnected and full-fill demands as well as energy storage, which subsequently formed a complex hybrid renewable energy system. Hence, forecasting of energy generation, sizing of equipment is essential for the economic feasibility of a complex hybrid system. Also necessary for the design analysis. Methodology: In this research article, the proposed Functional Link Convolutional Neural Network (FLCNN) is applied to forecast the energy generation from the hybrid solar and wind energy system. Also, the Jaya algorithm has been applied to find the optimal sizing of the solar and wind based hybrid renewable energy system. Results & Discussion: The proposed method is simple in design and implementation, and it also reduces computational complexity and time. The proposed FLCNN technique has been compared with various other Machine Learning (ML) methodology, such as Convolutional Neural Network (CNN), Random Forest (RF), and Xg-Boost. In sizing, Jaya is compared with other heuristic techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Cat Swarm Optimization (CSO). Conclusion: The proposed FLCNN and Jaya optimization techniques successfully applied for tasks like energy forecasting and sizing of the renewable energy system.


2020 ◽  
Vol 10 (12) ◽  
pp. 4061 ◽  
Author(s):  
Naoto Takatsu ◽  
Hooman Farzaneh

After the Great East Japan Earthquake, energy security and vulnerability have become critical issues facing the Japanese energy system. The integration of renewable energy sources to meet specific regional energy demand is a promising scenario to overcome these challenges. To this aim, this paper proposes a novel hydrogen-based hybrid renewable energy system (HRES), in which hydrogen fuel can be produced using both the methods of solar electrolysis and supercritical water gasification (SCWG) of biomass feedstock. The produced hydrogen is considered to function as an energy storage medium by storing renewable energy until the fuel cell converts it to electricity. The proposed HRES is used to meet the electricity demand load requirements for a typical household in a selected residential area located in Shinchi-machi in Fukuoka prefecture, Japan. The techno-economic assessment of deploying the proposed systems was conducted, using an integrated simulation-optimization modeling framework, considering two scenarios: (1) minimization of the total cost of the system in an off-grid mode and (2) maximization of the total profit obtained from using renewable electricity and selling surplus solar electricity to the grid, considering the feed-in-tariff (FiT) scheme in a grid-tied mode. As indicated by the model results, the proposed HRES can generate about 47.3 MWh of electricity in all scenarios, which is needed to meet the external load requirement in the selected study area. The levelized cost of energy (LCOE) of the system in scenarios 1 and 2 was estimated at 55.92 JPY/kWh and 56.47 JPY/kWh, respectively.


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