Analytical Modeling of Solar Cells

Mohammed Rasheed, Suha SHIHAB — Mon, 28 Oct 2019 00:51:58 +0000

In the present work, a modified method is utilized to find the real roots of nonlinear equations of a single-diode PV cell by combining the modified Aitken's extrapolation method (MAEM), Aitken's extrapolation method (AEM) and the Newton-Raphson method (NRM), describing, and comparing them. The extrapolation method (MAEM) and (AEM) in the form of Aitken –acceleration is applied for improvement the convergence of the iterative method (Newton-Raphson) technique. Using a new improve to Aitken technique on (NRM) enables one to obtain efficiently the numerical solution of the single-diode solar cell nonlinear equation. The speed of the proposed method is compared with two other methods by means of various values of load resistance (R) in the range between R ∈ [1, 5] and with the given voltage of the cell as an initial value in ambient temperature. The results showed that the proposed method (MAEM) is faster than the other methods (AEM and NRM).

A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic

Fatemehzahra Gholami Tirkolaei, Faramarz E. Seraji — Sun, 22 Dec 2019 21:15:32 +0000

Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.

There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.

In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.

Insight - Electronic

Analytical Modeling of Solar Cells

A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic