Modified Grid-Connected CSI for Hybrid PV/Wind Power Generation System

The principle of a power conditioning unit for hybrid PV/wind power generation system is proposed. The proposed power conditioner is based on the current source inverter (CSI) topology. All energy sources are connected in parallel with a DC-bus through the modified wave-shaping circuits. To achieve the unity power factor at the utility grid, the DC-link current can be controlled via the wave-shaping circuits with the sinusoidal PWM scheme. In this work, the carrier-based PWM scheme is also proposed to minimize the utility current THD. The power rating of the proposed system can be increased by connecting more PV/wind modules through their wave-shaping circuits in parallel with the other modules. The details of the operating principles, the system configurations, and the design considerations are described. The effectiveness of the proposed CSI is demonstrated by simulation results

Synthesis of compact wind profiles using evolutionary algorithms

In this paper, the authors face the problem of wind speed processing as environmental variable of a wind turbine system. Generally, the information on wind speed measurements is processed over long periods of time to be relevant with respect to the site characteristics (average and maximum speeds, statistics). Subsequent large scale profiles of wind speed lead to long processing time for simulation analysis and especially for optimization design that penalizes the search of optimal solutions. An original synthesis approach of a compact and representative wind speed profile using an Evolutionary Algorithm (EA) is proposed. This approach is compared to a purely statistical approach based on random number generators. It allows reducing the actual wind profile duration with compression ratios greater (two months of wind speed measurements are compressed in only 1 hour). Then, the synthesis approach by EA is applied to the sizing of an autonomous hybrid system based on wind turbine with battery storage for stand-alone energy systems. It has proven its effectiveness in reducing 200 days of wind speed measurements in only 10 days, allowing sizing the storage system with a significant gain in terms of computing time in the framework of the optimization process