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"Techno-economic feasibility analysis of Renewable-fed Power-to-Power (" by Zaib Shahid, M. Santarelli et al.

In this paper, the feasibility analysis of H2 and Battery based Power-to-Power (P2P) systems are presented from a techno-economic perspective. For this study, 21 small islands of France based in Europe are selected, being naturally endowed with renewable energy sources (RES) of solar and wind. For each island, three distinct energy storage options, i.e., hydrogen storage, battery storage and hydrogen + battery combined storage are discussed and explored. Optimum sizing of RES and P2P systems are achieved through employing particle swarm optimization (PSO) algorithm, keeping Levelized Cost of Energy (LCOE) as an objective function. The hydrogen and battery storage combination with an average LCOE value of 420Euro/MWh was found to be the most suitable option for all 21 reference islands. The associated Net Present Cost (NPC) was EUR564,388,050 which was lower than that for the other two storage options. The hybrid storage selection necessitated installation of 41 MW of photovoltaic (PV) ....

Levelized Cost Of Energy , Levelized Cost , Net Present Cost , Energy Storage Systems , French Islands , Greenhouse Gases , Particle Swarm Optimization , Ower To Power ,

"Swarm intelligence based localization in wireless sensor networks" by Junaid Akram, Arslan Javed et al.

Abstract
Wireless sensor networks (WSNs) increasingly penetrate our everyday life and are already employed in a wide range of application areas, such as habitat monitoring, precision agriculture, home automation, and logistics. Localization of sensor nodes in a network is a highly desirable capability in all these applications. The ability to precisely determine the position of nodes in sensor networks enables many new upcoming technologies such as robotics, automated driving, traffic monitoring, or inventory management. For all these applications, different requirements regarding accuracy, reliability, and speed of position estimation are posed. WSNs is a field with many optimization problems that have to be addressed. Optimization of power consumption of nodes in WSNs is the main problem that have to be addressed. WSN node has a limited power backup so this makes it a very critical issue. This paper formulates the concern on how WSNs can take advantage of the computational i ....

Particle Swarm Optimization , Swarm Intelligence , Wireless Sensor Network ,

"Force control of electro-active polymer actuators using model-free int" by Caner Sancak, Fatma Yamac et al.

Abstract
In this paper, a model-free control framework is proposed to control the tip force of a cantilevered trilayer CPA and similar cantilevered smart actuators. The proposed control method eliminates the requirement of modeling the CPAs in controller design for each application, and it is based on the online local estimation of the actuator dynamics. Due to the fact that the controller has few parameters to tune, this control method provides a relatively easy design and implementation process for the CPAs as compared to other model-free controllers. Although it is not vital, in order to optimize the controller performance, a meta-heuristic particle swarm optimization (PSO) algorithm, which utilizes an initial baseline model that approximates the CPAs dynamics, is used. The performance of the optimized controller is investigated in simulation and experimentally. Successful results are obtained with the proposed controller in terms of control performance, robustness, and rep ....

Artificial Muscle , Onducting Polymer Actuators , Lectro Active Polymer , Force Control , Ntelligent Pid , Odel Free Control , Particle Swarm Optimization ,

"A hybrid modified method of the sine cosine algorithm using latin hype" by Siti Rosli, Hasliza Rahim et al.

Publication Details
Rosli, S. J., Rahim, H. A., Abdul Rani, K. N., Ngadiran, R., Ahmad, R. B., Yahaya, N. Z., Abdulmalek, M., Jusoh, M., Yasin, M. N. M., Sabapathy, T. & Andrew, A. M. 2020, A hybrid modified method of the sine cosine algorithm using latin hypercube sampling with the cuckoo search algorithm for optimization problems , Electronics, vol. 9, no. 11, pp. 1-23.
Abstract
The metaheuristic algorithm is a popular research area for solving various optimization problems. In this study, we proposed two approaches based on the Sine Cosine Algorithm (SCA), namely, modification and hybridization. First, we attempted to solve the constraints of the original SCA by developing a modified SCA (MSCA) version with an improved identification capability of a random population using the Latin Hypercube Sampling (LHS) technique. MSCA serves to guide SCA in obtaining a better local optimum in the exploitation phase with fast convergence based on an optimum value of the solutio ....

Sine Cosine Algorithm , Latin Hypercube Sampling , Cuckoo Search Algorithm , Particle Swarm Optimization , Grey Wolf Optimization , Artificial Bee Colony , Gravitational Search Algorithm , Central Processing Unit , கொக்கு தேடல் வழிமுறை , துகள் திரள் தேர்வுமுறை , சாம்பல் ஓநாய் தேர்வுமுறை , செயற்கை தேனீ காலனி , ஈர்ப்பு தேடல் வழிமுறை , மைய ப்ரோஸெஸிஂக் அலகு ,