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The amount of solar energy incidence on a photovoltaic (PV) panel depends on the PV tilt angles with respect to the horizon. It is thus crucial to investigate the optimum tilt angles to maximise the efficiency of PV panels and at the same time to increase the performance of solar energy systems. The objective of this study is to estimate the optimum tilt angle for PV panels in order to collect the maximum solar radiation for the city of Dhahran in Saudi Arabia. A newly developed optimisation algorithm called the vortex search algorithm is used to estimate the solar radiation on the tilted surface. Moreover, one year can be divided into different periods in the proposed approach, and the optimum angle can be obtained for each one of these periods separately. The horizontal solar data (i.e. direct, diffuse and global solar radiation) is used to estimate the optimum tilt angle. The results demonstrate that the solar radiation estimated using the optimum tilt angle is maximised compared with the one estimated on a horizontal surface. [ABSTRACT FROM AUTHOR]

A new multi-objective method called Multi-Objective Electric Charged Particles Optimization (MOECPO) is proposed to optimally place wind turbines and at the same time select their optimal heights in an extensive area of wind farm considering several scenarios. This method permits the designer/planner to get several designs in just one run where the maximum efficiency and maximum output power are the objectives. Furthermore, while dealing with an optimization problem, reducing the number of design variables helps to simplify the problem and consequently improves the final solutions. In this paper, a smart approach which is based on binary coding is proposed and implemented for design variables reduction by a high factor. Under the scope of this research work, four case studies are investigated using two different sites and considering the same or different hub heights. The obtained Pareto set of solutions is represented by 96, 95, 199 and 209 solutions, for CASE 1, CASE 2, CASE3 and CASE 4, respectively. This front is spread over a large region and offers several interesting solutions with different number of turbines in the considered wind farm. The results or findings from the proposed approach allow the designer or planner to select the best solution or layout considering many factors. In addition, it can be used to plan the future extensions. • A new method to investigate the optimal location of wind turbines was proposed. • The optimization was done using multi-objective electric charged particles algorithm. • The multi-objective optimization was used to maximize efficiency and output power. • The smart approach was proposed and implemented for reducing design variables. • The results offer various solutions with different number of turbines in a wind farm. [ABSTRACT FROM AUTHOR]

Substituting a single large power grid into various manageable microgrids is the emerging form for maintaining power systems. A microgrid is usually comprised of small units of renewable energy sources, battery storage, combined heat and power (CHP) plants and most importantly, an energy management system (EMS). An EMS is responsible for the core functioning of a microgrid, which includes establishing continuous and reliable communication among all distributed generation (DG) units and ensuring well-coordinated activities. This research focuses on improving the performance of EMS. The problem at hand is the optimal scheduling of the generation units and battery storage in a microgrid. Therefore, EMS should ensure that the power is shared among different sources following an imposed scenario to meet the load requirements, while the operational costs of the microgrid are kept as low as possible. This problem is formulated as an optimization problem. To solve this problem, this research proposes an enhanced version of the most valuable player algorithm (MVPA) which is a new metaheuristic optimization algorithm, inspired by actual sporting events. The obtained results are compared with numerous well-known optimization algorithms to validate the efficiency of the proposed EMS. [ABSTRACT FROM AUTHOR]