We designed a system to produce atmospheric hybrid cold-discharge plasma (HCP) based on microcorona discharge on a single dielectric barrier and applied it to inactivate microorganisms that commonly attach the rice seed husk. The cold-plasma treatment modified the surface of the rice seeds, resulting in accelerated germination and enhanced water imbibition. The treatment can operate under air-based ambient conditions without the need for a vacuum. The cold-plasma treatment completely inactivated pathogenic fungi and other microorganisms, enhancing the germination percentage and seedling quality. The final germination percentage of the treated rice seeds was ∼98%, whereas that of the nontreated seeds was ∼90%. Microcorona discharge on a single dielectric barrier provides a nonaggressive cold plasma that can be applied to organic materials without causing thermal and electrical damage. The hybrid nonthermal plasma is cost effective and consumes relatively little power, making it suitable for the surface sterilization and disinfection of organic and biological materials with large-scale compatibility.

No abstract

This paper proposes an optimal generation scheduling method for a power system integrated with renewable energy sources (RES) based distributed generations (DG) and energy storage systems (ESS) considering maximum harvesting of RES outputs and minimum power system operating losses. The main contribution aims at economically employing RES in a power system. In particular, maximum harvesting of renewable energy is achieved by the mean of ESS management. In addition, minimum power system operating losses can be obtained by properly scheduling operating of ESS and controllable generations. Particle Swam Optimization (PSO) algorithm is applied to search for a near global optimal solutions. The optimization problem is formulated and evaluated taking into account power system operating constraints. The different operation scenarios have been used to investigate the effective of the proposed method via DIgSILENT PowerFactory software. The proposed method is examined with IEEE standard 14-bus and 30-bus test systems.

No abstract

Abstract--In order to achieve the optimal design based on some specific criteria by applying conventional techniques, sequence of design, selected location of PSSs are critical involved factors. This paper presents a method to simultaneously tune PSSs in multimachine power system using hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) based on multiobjective function comprising the damping ratio, damping factor and number of PSSs. First, the problem of selecting proper PSS parameters is converted to a simple multiobjective optimization problem. Then, the problem will be solved by a parallel micro GA based on HGA. The stabilizers are tuned to simultaneously shift the lightly damped and undamped oscillation modes to a specific stable zone in the splane and to self identify the appropriate choice of PSS locations by using eigenvalue-based multiobjective function. Many scenarios with different operating conditions have been included in the process of simultaneous tuning so as to guarantee the robustness and their performance. A 68-bus and 16-generator power system has been employed to validate the effectiveness of the proposed tuning method.Index Terms-Hierarchical genetic algorithm, multiobjective design, parallel micro genetic algorithm, power system stabilizer tuning.

No abstract

No abstract

No abstract